{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/random-resized-crop/papers/3","list_of":"/method/random-resized-crop","method":"Random Resized Crop","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":3,"pages_in_order":4,"rows_per_page":100,"rows":[201,300],"of":303,"counts":{"archive_papers_tagged":303,"with_a_code_link":190,"where_syntology_ran_a_sample":86,"not_listed_spam_title":0,"listed":303,"listed_where_code_ran":86,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":72,"every_run_a_failure_of_syntologys_instrument":14,"listed_with_a_run_with_no_instrument_failure":72,"listed_every_run_a_failure_of_syntologys_instrument":14,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/random-resized-crop","prev":"/method/random-resized-crop/papers/2","next":"/method/random-resized-crop/papers/4","papers":[{"paper":"/paper/with-a-little-help-from-my-friends-nearest","slug":"with-a-little-help-from-my-friends-nearest","title":"With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations","date":"2021-04-29","arxiv_id":"2104.14548","n_code_links":4,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"4 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","official":null}},{"paper":"/paper/patient-contrastive-learning-a-performant","slug":"patient-contrastive-learning-a-performant","title":"Patient Contrastive Learning: a Performant, Expressive, and Practical Approach to ECG Modeling","date":"2021-04-09","arxiv_id":"2104.04569","n_code_links":1,"syntology":null},{"paper":"/paper/towards-fine-grained-visual-representations","slug":"towards-fine-grained-visual-representations","title":"Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling","date":"2021-04-09","arxiv_id":"2104.04323","n_code_links":1,"syntology":null},{"paper":null,"slug":"does-your-dermatology-classifier-know-what-it","title":"Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions","date":"2021-04-08","arxiv_id":"2104.03829","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-supervised-learning-for-gastritis","title":"Self-Supervised Learning for Gastritis Detection with Gastric X-ray Images","date":"2021-04-07","arxiv_id":"2104.02864","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-representation-learning-for","slug":"benchmarking-representation-learning-for","title":"Benchmarking Representation Learning for Natural World Image Collections","date":"2021-03-30","arxiv_id":"2103.16483","n_code_links":1,"syntology":{"ran":7,"of":12,"n_ran_checked":7,"n_instrument":0,"unverified":5,"pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","official":{"repos":["visipedia/newt"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"classification-of-seeds-using-domain","title":"Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks","date":"2021-03-29","arxiv_id":"2103.15578","n_code_links":0,"syntology":null},{"paper":"/paper/self-supervised-representation-learning-on-2","slug":"self-supervised-representation-learning-on-2","title":"Self-supervised representation learning on manifolds","date":"2021-03-08","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/self-supervised-pretraining-of-visual","slug":"self-supervised-pretraining-of-visual","title":"Self-supervised Pretraining of Visual Features in the Wild","date":"2021-03-02","arxiv_id":"2103.01988","n_code_links":1,"syntology":null},{"paper":"/paper/sise-pc-semi-supervised-image-subsampling-for","slug":"sise-pc-semi-supervised-image-subsampling-for","title":"SISE-PC: Semi-supervised Image Subsampling for Explainable Pathology","date":"2021-02-23","arxiv_id":"2102.11560","n_code_links":1,"syntology":null},{"paper":null,"slug":"train-a-one-million-way-instance-classifier","title":"Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning","date":"2021-02-09","arxiv_id":"2102.04848","n_code_links":0,"syntology":null},{"paper":"/paper/bottleneck-transformers-for-visual","slug":"bottleneck-transformers-for-visual","title":"Bottleneck Transformers for Visual Recognition","date":"2021-01-27","arxiv_id":"2101.11605","n_code_links":13,"syntology":{"ran":26,"of":49,"n_ran_checked":19,"n_instrument":7,"unverified":23,"pointer_only":8,"phrase":"26 ran (of which 9 constructed an object rather than computing a result; 19 with no instrument failure: 1 honoured, 0 violated, 18 with no contract checked; 7 where Syntology's instrument failed) · 23 unverified","official":null}},{"paper":null,"slug":"self-supervised-representation-learning-from-3","title":"Self-Supervised Representation Learning from Flow Equivariance","date":"2021-01-16","arxiv_id":"2101.06553","n_code_links":0,"syntology":null},{"paper":null,"slug":"consistent-instance-classification-for","title":"Consistent Instance Classification for Unsupervised Representation Learning","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"fast-training-of-contrastive-learning-with","title":"Fast Training of Contrastive Learning with Intermediate Contrastive Loss","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/the-lottery-tickets-hypothesis-for-supervised","slug":"the-lottery-tickets-hypothesis-for-supervised","title":"The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models","date":"2020-12-12","arxiv_id":"2012.06908","n_code_links":1,"syntology":null},{"paper":"/paper/self-supervised-contrastive-learning-for-2","slug":"self-supervised-contrastive-learning-for-2","title":"Self supervised contrastive learning for digital histopathology","date":"2020-11-27","arxiv_id":"2011.13971","n_code_links":2,"syntology":null},{"paper":null,"slug":"beyond-single-instance-multi-view","title":"A Unified Mixture-View Framework for Unsupervised Representation Learning","date":"2020-11-26","arxiv_id":"2011.13356","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-contrastive-learning-in-human","slug":"exploring-contrastive-learning-in-human","title":"Exploring Contrastive Learning in Human Activity Recognition for Healthcare","date":"2020-11-23","arxiv_id":"2011.11542","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-domain-agnostic-contrastive-learning","title":"Towards Domain-Agnostic Contrastive Learning","date":"2020-11-09","arxiv_id":"2011.04419","n_code_links":0,"syntology":null},{"paper":"/paper/intriguing-properties-of-contrastive-losses","slug":"intriguing-properties-of-contrastive-losses","title":"Intriguing Properties of Contrastive Losses","date":"2020-11-05","arxiv_id":"2011.02803","n_code_links":3,"syntology":null},{"paper":"/paper/learning-visual-representations-for-transfer-1","slug":"learning-visual-representations-for-transfer-1","title":"Learning Visual Representations for Transfer Learning by Suppressing Texture","date":"2020-11-03","arxiv_id":"2011.01901","n_code_links":1,"syntology":null},{"paper":"/paper/speech-simclr-combining-contrastive-and","slug":"speech-simclr-combining-contrastive-and","title":"Speech SIMCLR: Combining Contrastive and Reconstruction Objective for Self-supervised Speech Representation Learning","date":"2020-10-27","arxiv_id":"2010.13991","n_code_links":1,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["athena-team/athena"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/neural-audio-fingerprint-for-high-specific","slug":"neural-audio-fingerprint-for-high-specific","title":"Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning","date":"2020-10-22","arxiv_id":"2010.11910","n_code_links":3,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["mimbres/neural-audio-fp"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/for-self-supervised-learning-rationality-1","slug":"for-self-supervised-learning-rationality-1","title":"For self-supervised learning, Rationality implies generalization, provably","date":"2020-10-16","arxiv_id":"2010.08508","n_code_links":2,"syntology":null},{"paper":null,"slug":"self-supervised-ranking-for-representation","title":"Self-Supervised Ranking for Representation Learning","date":"2020-10-14","arxiv_id":"2010.07258","n_code_links":0,"syntology":null},{"paper":"/paper/viewmaker-networks-learning-views-for-1","slug":"viewmaker-networks-learning-views-for-1","title":"Viewmaker Networks: Learning Views for Unsupervised Representation Learning","date":"2020-10-14","arxiv_id":"2010.07432","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["alextamkin/viewmaker"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/understanding-self-supervised-learning-with","slug":"understanding-self-supervised-learning-with","title":"Understanding Self-supervised Learning with Dual Deep Networks","date":"2020-10-01","arxiv_id":"2010.00578","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/luckmatters"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/g-simclr-self-supervised-contrastive-learning","slug":"g-simclr-self-supervised-contrastive-learning","title":"G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling","date":"2020-09-28","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/g-simclr-self-supervised-contrastive-learning-1","slug":"g-simclr-self-supervised-contrastive-learning-1","title":"G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling","date":"2020-09-25","arxiv_id":"2009.12007","n_code_links":1,"syntology":null},{"paper":"/paper/aag-self-supervised-representation-learning","slug":"aag-self-supervised-representation-learning","title":"AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent Loss","date":"2020-09-17","arxiv_id":"2009.07994","n_code_links":3,"syntology":null},{"paper":"/paper/a-framework-for-contrastive-self-supervised","slug":"a-framework-for-contrastive-self-supervised","title":"A Framework For Contrastive Self-Supervised Learning And Designing A New Approach","date":"2020-08-31","arxiv_id":"2009.00104","n_code_links":2,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":null}},{"paper":"/paper/spatiotemporal-contrastive-video","slug":"spatiotemporal-contrastive-video","title":"Spatiotemporal Contrastive Video Representation Learning","date":"2020-08-09","arxiv_id":"2008.03800","n_code_links":4,"syntology":null},{"paper":"/paper/unsupervised-feature-learning-by-cross-level","slug":"unsupervised-feature-learning-by-cross-level","title":"Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination","date":"2020-08-09","arxiv_id":"2008.03813","n_code_links":2,"syntology":{"ran":6,"of":8,"n_ran_checked":4,"n_instrument":2,"unverified":2,"pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["frank-xwang/CLD-UnsupervisedLearning"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/parametric-instance-classification-for","slug":"parametric-instance-classification-for","title":"Parametric Instance Classification for Unsupervised Visual Feature Learning","date":"2020-06-25","arxiv_id":"2006.14618","n_code_links":1,"syntology":null},{"paper":"/paper/clocs-contrastive-learning-of-cardiac-signals","slug":"clocs-contrastive-learning-of-cardiac-signals","title":"CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients","date":"2020-05-27","arxiv_id":"2005.13249","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["danikiyasseh/CLOCS"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/learning-to-classify-images-without-labels","slug":"learning-to-classify-images-without-labels","title":"SCAN: Learning to Classify Images without Labels","date":"2020-05-25","arxiv_id":"2005.12320","n_code_links":2,"syntology":null},{"paper":"/paper/resnest-split-attention-networks","slug":"resnest-split-attention-networks","title":"ResNeSt: Split-Attention Networks","date":"2020-04-19","arxiv_id":"2004.08955","n_code_links":36,"syntology":{"ran":28,"of":48,"n_ran_checked":25,"n_instrument":3,"unverified":20,"pointer_only":23,"phrase":"28 ran (of which 0 constructed an object rather than computing a result; 25 with no instrument failure: 0 honoured, 0 violated, 25 with no contract checked; 3 where Syntology's instrument failed) · 20 unverified","official":{"repos":["zhanghang1989/ResNeSt"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/fixing-the-train-test-resolution-discrepancy-2","slug":"fixing-the-train-test-resolution-discrepancy-2","title":"Fixing the train-test resolution discrepancy: FixEfficientNet","date":"2020-03-18","arxiv_id":"2003.08237","n_code_links":1,"syntology":null},{"paper":"/paper/rethinking-image-mixture-for-unsupervised","slug":"rethinking-image-mixture-for-unsupervised","title":"Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning","date":"2020-03-11","arxiv_id":"2003.05438","n_code_links":3,"syntology":{"ran":3,"of":4,"n_ran_checked":0,"n_instrument":3,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","official":{"repos":["szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning","szq0214/un-mix"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/improved-baselines-with-momentum-contrastive","slug":"improved-baselines-with-momentum-contrastive","title":"Improved Baselines with Momentum Contrastive Learning","date":"2020-03-09","arxiv_id":"2003.04297","n_code_links":36,"syntology":{"ran":28,"of":43,"n_ran_checked":21,"n_instrument":7,"unverified":15,"pointer_only":15,"phrase":"28 ran (of which 0 constructed an object rather than computing a result; 21 with no instrument failure: 0 honoured, 1 violated, 20 with no contract checked; 7 where Syntology's instrument failed) · 15 unverified","official":{"repos":["facebookresearch/moco"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/maxup-a-simple-way-to-improve-generalization","slug":"maxup-a-simple-way-to-improve-generalization","title":"MaxUp: A Simple Way to Improve Generalization of Neural Network Training","date":"2020-02-20","arxiv_id":"2002.09024","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":null}},{"paper":"/paper/a-simple-framework-for-contrastive-learning","slug":"a-simple-framework-for-contrastive-learning","title":"A Simple Framework for Contrastive Learning of Visual Representations","date":"2020-02-13","arxiv_id":"2002.05709","n_code_links":96,"syntology":{"ran":115,"of":137,"n_ran_checked":90,"n_instrument":25,"unverified":22,"pointer_only":52,"phrase":"115 ran (of which 33 constructed an object rather than computing a result; 90 with no instrument failure: 1 honoured, 1 violated, 88 with no contract checked; 25 where Syntology's instrument failed) · 22 unverified","official":{"repos":["google-research/simclr"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/harmonic-convolutional-networks-based-on","slug":"harmonic-convolutional-networks-based-on","title":"Harmonic Convolutional Networks based on Discrete Cosine Transform","date":"2020-01-18","arxiv_id":"2001.06570","n_code_links":1,"syntology":{"ran":10,"of":10,"n_ran_checked":10,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["matej-ulicny/harmonic-networks"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/compounding-the-performance-improvements-of","slug":"compounding-the-performance-improvements-of","title":"Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network","date":"2020-01-17","arxiv_id":"2001.06268","n_code_links":1,"syntology":{"ran":3,"of":11,"n_ran_checked":2,"n_instrument":1,"unverified":8,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","official":{"repos":["clovaai/assembled-cnn"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":"/paper/large-scale-learning-of-general-visual","slug":"large-scale-learning-of-general-visual","title":"Big Transfer (BiT): General Visual Representation Learning","date":"2019-12-24","arxiv_id":"1912.11370","n_code_links":9,"syntology":{"ran":9,"of":10,"n_ran_checked":7,"n_instrument":2,"unverified":1,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["google-research/big_transfer"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/spinenet-learning-scale-permuted-backbone-for","slug":"spinenet-learning-scale-permuted-backbone-for","title":"SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization","date":"2019-12-10","arxiv_id":"1912.05027","n_code_links":13,"syntology":null},{"paper":"/paper/ghostnet-more-features-from-cheap-operations","slug":"ghostnet-more-features-from-cheap-operations","title":"GhostNet: More Features from Cheap Operations","date":"2019-11-27","arxiv_id":"1911.11907","n_code_links":33,"syntology":{"ran":19,"of":23,"n_ran_checked":16,"n_instrument":3,"unverified":4,"pointer_only":5,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 2 honoured, 0 violated, 14 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified","official":{"repos":["huawei-noah/ghostnet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/momentum-contrast-for-unsupervised-visual","slug":"momentum-contrast-for-unsupervised-visual","title":"Momentum Contrast for Unsupervised Visual Representation Learning","date":"2019-11-13","arxiv_id":"1911.05722","n_code_links":44,"syntology":{"ran":28,"of":42,"n_ran_checked":23,"n_instrument":5,"unverified":14,"pointer_only":19,"phrase":"28 ran (of which 16 constructed an object rather than computing a result; 23 with no instrument failure: 0 honoured, 0 violated, 23 with no contract checked; 5 where Syntology's instrument failed) · 14 unverified","official":{"repos":["facebookresearch/moco","ppwwyyxx/moco.tensorflow"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/eca-net-efficient-channel-attention-for-deep","slug":"eca-net-efficient-channel-attention-for-deep","title":"ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks","date":"2019-10-08","arxiv_id":"1910.03151","n_code_links":13,"syntology":{"ran":3,"of":8,"n_ran_checked":2,"n_instrument":1,"unverified":5,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","official":{"repos":["BangguWu/ECANet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":"/paper/deformable-kernels-adapting-effective","slug":"deformable-kernels-adapting-effective","title":"Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation","date":"2019-10-07","arxiv_id":"1910.02940","n_code_links":2,"syntology":null},{"paper":"/paper/randaugment-practical-data-augmentation-with","slug":"randaugment-practical-data-augmentation-with","title":"RandAugment: Practical automated data augmentation with a reduced search space","date":"2019-09-30","arxiv_id":"1909.13719","n_code_links":19,"syntology":{"ran":58,"of":65,"n_ran_checked":7,"n_instrument":51,"unverified":7,"pointer_only":17,"phrase":"58 ran (of which 1 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 51 where Syntology's instrument failed) · 7 unverified","official":null}},{"paper":"/paper/attentive-normalization","slug":"attentive-normalization","title":"Attentive Normalization","date":"2019-08-04","arxiv_id":"1908.01259","n_code_links":2,"syntology":null},{"paper":"/paper/compact-global-descriptor-for-neural-networks","slug":"compact-global-descriptor-for-neural-networks","title":"Compact Global Descriptor for Neural Networks","date":"2019-07-23","arxiv_id":"1907.09665","n_code_links":1,"syntology":null},{"paper":"/paper/densely-connected-search-space-for-more","slug":"densely-connected-search-space-for-more","title":"Densely Connected Search Space for More Flexible Neural Architecture Search","date":"2019-06-23","arxiv_id":"1906.09607","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["JaminFong/DenseNAS"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/fixing-the-train-test-resolution-discrepancy","slug":"fixing-the-train-test-resolution-discrepancy","title":"Fixing the train-test resolution discrepancy","date":"2019-06-14","arxiv_id":"1906.06423","n_code_links":3,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"0 ran · 2 unverified","official":{"repos":["facebookresearch/FixRes"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"paper":"/paper/contrastive-multiview-coding","slug":"contrastive-multiview-coding","title":"Contrastive Multiview Coding","date":"2019-06-13","arxiv_id":"1906.05849","n_code_links":8,"syntology":{"ran":4,"of":4,"n_ran_checked":2,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["HobbitLong/CMC"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/spatial-group-wise-enhance-improving-semantic","slug":"spatial-group-wise-enhance-improving-semantic","title":"Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks","date":"2019-05-23","arxiv_id":"1905.09646","n_code_links":3,"syntology":{"ran":2,"of":4,"n_ran_checked":0,"n_instrument":2,"unverified":2,"pointer_only":4,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["implus/PytorchInsight"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/data-efficient-image-recognition-with","slug":"data-efficient-image-recognition-with","title":"Data-Efficient Image Recognition with Contrastive Predictive Coding","date":"2019-05-22","arxiv_id":"1905.09272","n_code_links":4,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/searching-for-mobilenetv3","slug":"searching-for-mobilenetv3","title":"Searching for MobileNetV3","date":"2019-05-06","arxiv_id":"1905.02244","n_code_links":67,"syntology":{"ran":86,"of":105,"n_ran_checked":75,"n_instrument":11,"unverified":19,"pointer_only":46,"phrase":"86 ran (of which 22 constructed an object rather than computing a result; 75 with no instrument failure: 6 honoured, 2 violated, 67 with no contract checked; 11 where Syntology's instrument failed) · 19 unverified","official":null}},{"paper":"/paper/gcnet-non-local-networks-meet-squeeze","slug":"gcnet-non-local-networks-meet-squeeze","title":"GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond","date":"2019-04-25","arxiv_id":"1904.11492","n_code_links":9,"syntology":null},{"paper":"/paper/190409925","slug":"190409925","title":"Attention Augmented Convolutional Networks","date":"2019-04-22","arxiv_id":"1904.09925","n_code_links":14,"syntology":{"ran":3,"of":6,"n_ran_checked":1,"n_instrument":2,"unverified":3,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":null}},{"paper":"/paper/190409460","slug":"190409460","title":"Data-Driven Neuron Allocation for Scale Aggregation Networks","date":"2019-04-20","arxiv_id":"1904.09460","n_code_links":1,"syntology":null},{"paper":"/paper/190408900","slug":"190408900","title":"CornerNet-Lite: Efficient Keypoint Based Object Detection","date":"2019-04-18","arxiv_id":"1904.08900","n_code_links":6,"syntology":{"ran":21,"of":27,"n_ran_checked":21,"n_instrument":0,"unverified":6,"pointer_only":0,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 21 with no instrument failure: 1 honoured, 0 violated, 20 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","official":{"repos":["princeton-vl/CornerNet-Lite"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":4,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/exploring-randomly-wired-neural-networks-for","slug":"exploring-randomly-wired-neural-networks-for","title":"Exploring Randomly Wired Neural Networks for Image Recognition","date":"2019-04-02","arxiv_id":"1904.01569","n_code_links":9,"syntology":{"ran":10,"of":31,"n_ran_checked":10,"n_instrument":0,"unverified":21,"pointer_only":1,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 21 unverified","official":null}},{"paper":"/paper/res2net-a-new-multi-scale-backbone","slug":"res2net-a-new-multi-scale-backbone","title":"Res2Net: A New Multi-scale Backbone Architecture","date":"2019-04-02","arxiv_id":"1904.01169","n_code_links":34,"syntology":{"ran":5,"of":9,"n_ran_checked":3,"n_instrument":2,"unverified":4,"pointer_only":9,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","official":null}},{"paper":"/paper/srm-a-style-based-recalibration-module-for","slug":"srm-a-style-based-recalibration-module-for","title":"SRM : A Style-based Recalibration Module for Convolutional Neural Networks","date":"2019-03-26","arxiv_id":"1903.10829","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/multigrain-a-unified-image-embedding-for","slug":"multigrain-a-unified-image-embedding-for","title":"MultiGrain: a unified image embedding for classes and instances","date":"2019-02-14","arxiv_id":"1902.05509","n_code_links":3,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/multigrain"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/bottom-up-object-detection-by-grouping","slug":"bottom-up-object-detection-by-grouping","title":"Bottom-up Object Detection by Grouping Extreme and Center Points","date":"2019-01-23","arxiv_id":"1901.08043","n_code_links":2,"syntology":{"ran":1,"of":5,"n_ran_checked":1,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["xingyizhou/ExtremeNet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/elastic-improving-cnns-with-instance-specific","slug":"elastic-improving-cnns-with-instance-specific","title":"ELASTIC: Improving CNNs with Dynamic Scaling Policies","date":"2018-12-13","arxiv_id":"1812.05262","n_code_links":1,"syntology":{"ran":3,"of":10,"n_ran_checked":2,"n_instrument":1,"unverified":7,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 7 unverified","official":{"repos":["allenai/elastic"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":7,"ran_from_kinds":["official"]}}},{"paper":"/paper/fbnet-hardware-aware-efficient-convnet-design","slug":"fbnet-hardware-aware-efficient-convnet-design","title":"FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search","date":"2018-12-09","arxiv_id":"1812.03443","n_code_links":5,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/mobile-vision"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/bag-of-tricks-for-image-classification-with","slug":"bag-of-tricks-for-image-classification-with","title":"Bag of Tricks for Image Classification with Convolutional Neural Networks","date":"2018-12-04","arxiv_id":"1812.01187","n_code_links":28,"syntology":{"ran":11,"of":15,"n_ran_checked":9,"n_instrument":2,"unverified":4,"pointer_only":5,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 2 honoured, 0 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","official":{"repos":["dmlc/gluon-cv"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/espnetv2-a-light-weight-power-efficient-and","slug":"espnetv2-a-light-weight-power-efficient-and","title":"ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network","date":"2018-11-28","arxiv_id":"1811.11431","n_code_links":10,"syntology":{"ran":4,"of":4,"n_ran_checked":2,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["sacmehta/EdgeNets"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/cornernet-detecting-objects-as-paired","slug":"cornernet-detecting-objects-as-paired","title":"CornerNet: Detecting Objects as Paired Keypoints","date":"2018-08-03","arxiv_id":"1808.01244","n_code_links":5,"syntology":{"ran":3,"of":11,"n_ran_checked":1,"n_instrument":2,"unverified":8,"pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 8 unverified","official":{"repos":["princeton-vl/CornerNet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":"/paper/mnasnet-platform-aware-neural-architecture","slug":"mnasnet-platform-aware-neural-architecture","title":"MnasNet: Platform-Aware Neural Architecture Search for Mobile","date":"2018-07-31","arxiv_id":"1807.11626","n_code_links":29,"syntology":{"ran":4,"of":6,"n_ran_checked":3,"n_instrument":1,"unverified":2,"pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["tensorflow/tpu"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/cbam-convolutional-block-attention-module","slug":"cbam-convolutional-block-attention-module","title":"CBAM: Convolutional Block Attention Module","date":"2018-07-17","arxiv_id":"1807.06521","n_code_links":31,"syntology":{"ran":13,"of":22,"n_ran_checked":10,"n_instrument":3,"unverified":9,"pointer_only":3,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 3 where Syntology's instrument failed) · 9 unverified","official":null}},{"paper":"/paper/big-little-net-an-efficient-multi-scale","slug":"big-little-net-an-efficient-multi-scale","title":"Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition","date":"2018-07-10","arxiv_id":"1807.03848","n_code_links":3,"syntology":null},{"paper":"/paper/exploring-the-limits-of-weakly-supervised","slug":"exploring-the-limits-of-weakly-supervised","title":"Exploring the Limits of Weakly Supervised Pretraining","date":"2018-05-02","arxiv_id":"1805.00932","n_code_links":4,"syntology":null},{"paper":"/paper/espnet-efficient-spatial-pyramid-of-dilated","slug":"espnet-efficient-spatial-pyramid-of-dilated","title":"ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation","date":"2018-03-19","arxiv_id":"1803.06815","n_code_links":8,"syntology":{"ran":9,"of":10,"n_ran_checked":7,"n_instrument":2,"unverified":1,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 2 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["sacmehta/ESPNet"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed"]}}},{"paper":"/paper/a-closer-look-at-spatiotemporal-convolutions","slug":"a-closer-look-at-spatiotemporal-convolutions","title":"A Closer Look at Spatiotemporal Convolutions for Action Recognition","date":"2017-11-30","arxiv_id":"1711.11248","n_code_links":24,"syntology":{"ran":1,"of":4,"n_ran_checked":0,"n_instrument":1,"unverified":3,"pointer_only":4,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["facebookresearch/R2Plus1D"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/squeeze-and-excitation-networks","slug":"squeeze-and-excitation-networks","title":"Squeeze-and-Excitation Networks","date":"2017-09-05","arxiv_id":"1709.01507","n_code_links":85,"syntology":{"ran":2,"of":9,"n_ran_checked":0,"n_instrument":2,"unverified":7,"pointer_only":6,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 7 unverified","official":{"repos":["hujie-frank/SENet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/dual-path-networks","slug":"dual-path-networks","title":"Dual Path Networks","date":"2017-07-06","arxiv_id":"1707.01629","n_code_links":18,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/shufflenet-an-extremely-efficient","slug":"shufflenet-an-extremely-efficient","title":"ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices","date":"2017-07-04","arxiv_id":"1707.01083","n_code_links":38,"syntology":null},{"paper":"/paper/mobilenets-efficient-convolutional-neural","slug":"mobilenets-efficient-convolutional-neural","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","date":"2017-04-17","arxiv_id":"1704.04861","n_code_links":159,"syntology":{"ran":53,"of":83,"n_ran_checked":44,"n_instrument":9,"unverified":30,"pointer_only":48,"phrase":"53 ran (of which 28 constructed an object rather than computing a result; 44 with no instrument failure: 4 honoured, 0 violated, 40 with no contract checked; 9 where Syntology's instrument failed) · 30 unverified","official":{"repos":["tensorflow/tensorflow"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/active-convolution-learning-the-shape-of","slug":"active-convolution-learning-the-shape-of","title":"Active Convolution: Learning the Shape of Convolution for Image Classification","date":"2017-03-27","arxiv_id":"1703.09076","n_code_links":1,"syntology":null},{"paper":"/paper/yolo9000-better-faster-stronger","slug":"yolo9000-better-faster-stronger","title":"YOLO9000: Better, Faster, Stronger","date":"2016-12-25","arxiv_id":"1612.08242","n_code_links":231,"syntology":{"ran":44,"of":60,"n_ran_checked":33,"n_instrument":11,"unverified":16,"pointer_only":23,"phrase":"44 ran (of which 0 constructed an object rather than computing a result; 33 with no instrument failure: 1 honoured, 4 violated, 28 with no contract checked; 11 where Syntology's instrument failed) · 16 unverified","official":null}},{"paper":"/paper/image-to-image-translation-with-conditional","slug":"image-to-image-translation-with-conditional","title":"Image-to-Image Translation with Conditional Adversarial Networks","date":"2016-11-21","arxiv_id":"1611.07004","n_code_links":192,"syntology":{"ran":74,"of":122,"n_ran_checked":68,"n_instrument":6,"unverified":48,"pointer_only":10,"phrase":"74 ran (of which 0 constructed an object rather than computing a result; 68 with no instrument failure: 4 honoured, 4 violated, 60 with no contract checked; 6 where Syntology's instrument failed) · 48 unverified","official":null}},{"paper":"/paper/aggregated-residual-transformations-for-deep","slug":"aggregated-residual-transformations-for-deep","title":"Aggregated Residual Transformations for Deep Neural Networks","date":"2016-11-16","arxiv_id":"1611.05431","n_code_links":61,"syntology":{"ran":51,"of":80,"n_ran_checked":31,"n_instrument":20,"unverified":29,"pointer_only":13,"phrase":"51 ran (of which 7 constructed an object rather than computing a result; 31 with no instrument failure: 0 honoured, 0 violated, 31 with no contract checked; 20 where Syntology's instrument failed) · 29 unverified","official":{"repos":["facebookresearch/ResNeXt"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/deep-pyramidal-residual-networks","slug":"deep-pyramidal-residual-networks","title":"Deep Pyramidal Residual Networks","date":"2016-10-10","arxiv_id":"1610.02915","n_code_links":7,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["jhkim89/PyramidNet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/fractalnet-ultra-deep-neural-networks-without","slug":"fractalnet-ultra-deep-neural-networks-without","title":"FractalNet: Ultra-Deep Neural Networks without Residuals","date":"2016-05-24","arxiv_id":"1605.07648","n_code_links":4,"syntology":{"ran":4,"of":6,"n_ran_checked":0,"n_instrument":4,"unverified":2,"pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":"/paper/wide-residual-networks","slug":"wide-residual-networks","title":"Wide Residual Networks","date":"2016-05-23","arxiv_id":"1605.07146","n_code_links":72,"syntology":{"ran":66,"of":96,"n_ran_checked":48,"n_instrument":18,"unverified":30,"pointer_only":50,"phrase":"66 ran (of which 31 constructed an object rather than computing a result; 48 with no instrument failure: 0 honoured, 0 violated, 48 with no contract checked; 18 where Syntology's instrument failed) · 30 unverified","official":{"repos":["szagoruyko/wide-residual-networks"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["listed","official","unlocated"]}}},{"paper":"/paper/identity-mappings-in-deep-residual-networks","slug":"identity-mappings-in-deep-residual-networks","title":"Identity Mappings in Deep Residual Networks","date":"2016-03-16","arxiv_id":"1603.05027","n_code_links":54,"syntology":{"ran":14,"of":25,"n_ran_checked":12,"n_instrument":2,"unverified":11,"pointer_only":2,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 1 honoured, 0 violated, 11 with no contract checked; 2 where Syntology's instrument failed) · 11 unverified","official":{"repos":["KaimingHe/resnet-1k-layers"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/deep-residual-learning-for-image-recognition","slug":"deep-residual-learning-for-image-recognition","title":"Deep Residual Learning for Image Recognition","date":"2015-12-10","arxiv_id":"1512.03385","n_code_links":484,"syntology":{"ran":254,"of":377,"n_ran_checked":166,"n_instrument":88,"unverified":123,"pointer_only":193,"phrase":"254 ran (of which 108 constructed an object rather than computing a result; 166 with no instrument failure: 3 honoured, 1 violated, 162 with no contract checked; 88 where Syntology's instrument failed) · 123 unverified","official":{"repos":["KaimingHe/resnet-1k-layers"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/you-only-look-once-unified-real-time-object","slug":"you-only-look-once-unified-real-time-object","title":"You Only Look Once: Unified, Real-Time Object Detection","date":"2015-06-08","arxiv_id":"1506.02640","n_code_links":144,"syntology":{"ran":89,"of":148,"n_ran_checked":59,"n_instrument":30,"unverified":59,"pointer_only":98,"phrase":"89 ran (of which 27 constructed an object rather than computing a result; 59 with no instrument failure: 4 honoured, 4 violated, 51 with no contract checked; 30 where Syntology's instrument failed) · 59 unverified","official":null}},{"paper":"/paper/batch-normalization-accelerating-deep-network","slug":"batch-normalization-accelerating-deep-network","title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","date":"2015-02-11","arxiv_id":"1502.03167","n_code_links":70,"syntology":{"ran":19,"of":21,"n_ran_checked":14,"n_instrument":5,"unverified":2,"pointer_only":5,"phrase":"19 ran (of which 5 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 5 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":"/paper/delving-deep-into-rectifiers-surpassing-human","slug":"delving-deep-into-rectifiers-surpassing-human","title":"Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification","date":"2015-02-06","arxiv_id":"1502.01852","n_code_links":15,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/going-deeper-with-convolutions","slug":"going-deeper-with-convolutions","title":"Going Deeper with Convolutions","date":"2014-09-17","arxiv_id":"1409.4842","n_code_links":83,"syntology":{"ran":34,"of":42,"n_ran_checked":30,"n_instrument":4,"unverified":8,"pointer_only":21,"phrase":"34 ran (of which 19 constructed an object rather than computing a result; 30 with no instrument failure: 0 honoured, 0 violated, 30 with no contract checked; 4 where Syntology's instrument failed) · 8 unverified","official":{"repos":["worksheets.codalab.org/worksheets/0xbcd424d2bf544c4786efcc0063759b1a"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/very-deep-convolutional-networks-for-large","slug":"very-deep-convolutional-networks-for-large","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","date":"2014-09-04","arxiv_id":"1409.1556","n_code_links":305,"syntology":{"ran":81,"of":122,"n_ran_checked":71,"n_instrument":10,"unverified":41,"pointer_only":8,"phrase":"81 ran (of which 0 constructed an object rather than computing a result; 71 with no instrument failure: 0 honoured, 0 violated, 71 with no contract checked; 10 where Syntology's instrument failed) · 41 unverified","official":null}},{"paper":"/paper/spatial-pyramid-pooling-in-deep-convolutional","slug":"spatial-pyramid-pooling-in-deep-convolutional","title":"Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition","date":"2014-06-18","arxiv_id":"1406.4729","n_code_links":14,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":null}},{"paper":"/paper/overfeat-integrated-recognition-localization","slug":"overfeat-integrated-recognition-localization","title":"OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks","date":"2013-12-21","arxiv_id":"1312.6229","n_code_links":4,"syntology":null}],"record_sha256":"df11baaa1ef7d39bd1e7341c7609077a8b3c6e66db9652e5c866110c25af5082","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}