{"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/1x1-convolution/papers/21","list_of":"/method/1x1-convolution","method":"1x1 Convolution","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":21,"pages_in_order":57,"rows_per_page":100,"rows":[2001,2100],"of":5640,"counts":{"archive_papers_tagged":5640,"with_a_code_link":2516,"where_syntology_ran_a_sample":651,"not_listed_spam_title":0,"listed":5640,"listed_where_code_ran":651,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":545,"every_run_a_failure_of_syntologys_instrument":106,"listed_with_a_run_with_no_instrument_failure":545,"listed_every_run_a_failure_of_syntologys_instrument":106,"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/1x1-convolution","prev":"/method/1x1-convolution/papers/20","next":"/method/1x1-convolution/papers/22","papers":[{"paper":null,"slug":"heat-source-layout-optimization-using","title":"Heat Source Layout Optimization Using Automatic Deep Learning Surrogate and Multimodal Neighborhood Search Algorithm","date":"2022-05-16","arxiv_id":"2205.07812","n_code_links":0,"syntology":null},{"paper":"/paper/pillarnet-high-performance-pillar-based-3d","slug":"pillarnet-high-performance-pillar-based-3d","title":"PillarNet: Real-Time and High-Performance Pillar-based 3D Object Detection","date":"2022-05-16","arxiv_id":"2205.07403","n_code_links":1,"syntology":null},{"paper":null,"slug":"real-time-semantic-segmentation-on-fpgas-for","title":"Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml","date":"2022-05-16","arxiv_id":"2205.07690","n_code_links":0,"syntology":null},{"paper":null,"slug":"analyzing-lottery-ticket-hypothesis-from-pac","title":"Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective","date":"2022-05-15","arxiv_id":"2205.07320","n_code_links":0,"syntology":null},{"paper":"/paper/cmelgan-an-efficient-conditional-generative","slug":"cmelgan-an-efficient-conditional-generative","title":"cMelGAN: An Efficient Conditional Generative Model Based on Mel Spectrograms","date":"2022-05-15","arxiv_id":"2205.07319","n_code_links":1,"syntology":null},{"paper":null,"slug":"fused-deep-neural-network-based-transfer","title":"Fused Deep Neural Network based Transfer Learning in Occluded Face Classification and Person re-Identification","date":"2022-05-15","arxiv_id":"2205.07203","n_code_links":0,"syntology":null},{"paper":"/paper/guidelines-for-the-regularization-of-gammas","slug":"guidelines-for-the-regularization-of-gammas","title":"Guidelines for the Regularization of Gammas in Batch Normalization for Deep Residual Networks","date":"2022-05-15","arxiv_id":"2205.07260","n_code_links":0,"syntology":null},{"paper":null,"slug":"novel-multicolumn-kernel-extreme-learning","title":"Novel Multicolumn Kernel Extreme Learning Machine for Food Detection via Optimal Features from CNN","date":"2022-05-15","arxiv_id":"2205.07348","n_code_links":0,"syntology":null},{"paper":"/paper/classification-of-astronomical-bodies-by","slug":"classification-of-astronomical-bodies-by","title":"Classification of Astronomical Bodies by Efficient Layer Fine-Tuning of Deep Neural Networks","date":"2022-05-14","arxiv_id":"2205.07124","n_code_links":1,"syntology":null},{"paper":"/paper/efficient-deep-learning-methods-for","slug":"efficient-deep-learning-methods-for","title":"Efficient Deep Learning Methods for Identification of Defective Casting Products","date":"2022-05-14","arxiv_id":"2205.07118","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-modal-curb-detection-and-filtering","title":"Multi-modal curb detection and filtering","date":"2022-05-14","arxiv_id":"2205.07096","n_code_links":0,"syntology":null},{"paper":null,"slug":"revisiting-facial-key-point-detection-an","title":"Revisiting Facial Key Point Detection: An Efficient Approach Using Deep Neural Networks","date":"2022-05-14","arxiv_id":"2205.07121","n_code_links":0,"syntology":null},{"paper":null,"slug":"infrared-invisible-clothing-hiding-from","title":"Infrared Invisible Clothing:Hiding from Infrared Detectors at Multiple Angles in Real World","date":"2022-05-12","arxiv_id":"2205.05909","n_code_links":0,"syntology":null},{"paper":"/paper/identical-image-retrieval-using-deep-learning","slug":"identical-image-retrieval-using-deep-learning","title":"Identical Image Retrieval using Deep Learning","date":"2022-05-10","arxiv_id":"2205.04883","n_code_links":1,"syntology":null},{"paper":null,"slug":"object-detection-in-indian-food-platters","title":"Object Detection in Indian Food Platters using Transfer Learning with YOLOv4","date":"2022-05-10","arxiv_id":"2205.04841","n_code_links":0,"syntology":null},{"paper":null,"slug":"smartsage-training-large-scale-graph-neural","title":"SmartSAGE: Training Large-scale Graph Neural Networks using In-Storage Processing Architectures","date":"2022-05-10","arxiv_id":"2205.04711","n_code_links":0,"syntology":null},{"paper":"/paper/the-impact-of-partial-occlusion-on-pedestrian","slug":"the-impact-of-partial-occlusion-on-pedestrian","title":"The Impact of Partial Occlusion on Pedestrian Detectability","date":"2022-05-10","arxiv_id":"2205.04812","n_code_links":2,"syntology":null},{"paper":null,"slug":"using-frequency-attention-to-make-adversarial","title":"Using Frequency Attention to Make Adversarial Patch Powerful Against Person Detector","date":"2022-05-10","arxiv_id":"2205.04638","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-effective-scheme-for-maize-disease","title":"An Effective Scheme for Maize Disease Recognition based on Deep Networks","date":"2022-05-09","arxiv_id":"2205.04234","n_code_links":0,"syntology":null},{"paper":"/paper/hierattn-effectively-learn-representations","slug":"hierattn-effectively-learn-representations","title":"Deeply Supervised Skin Lesions Diagnosis with Stage and Branch Attention","date":"2022-05-09","arxiv_id":"2205.04326","n_code_links":2,"syntology":null},{"paper":"/paper/object-detection-with-spiking-neural-networks","slug":"object-detection-with-spiking-neural-networks","title":"Object Detection with Spiking Neural Networks on Automotive Event Data","date":"2022-05-09","arxiv_id":"2205.04339","n_code_links":1,"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":["loiccordone/object-detection-with-spiking-neural-networks"],"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/a-nas-neural-architecture-search-using","slug":"a-nas-neural-architecture-search-using","title":"Neural Architecture Search using Property Guided Synthesis","date":"2022-05-08","arxiv_id":"2205.03960","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-nt-xent-loss-upper-bound","title":"The NT-Xent loss upper bound","date":"2022-05-06","arxiv_id":"2205.03169","n_code_links":0,"syntology":null},{"paper":null,"slug":"biologically-inspired-deep-residual-networks","title":"Biologically inspired deep residual networks for computer vision applications","date":"2022-05-05","arxiv_id":"2205.02551","n_code_links":0,"syntology":null},{"paper":"/paper/text-to-artistic-image-generation","slug":"text-to-artistic-image-generation","title":"Text to artistic image generation","date":"2022-05-05","arxiv_id":"2205.02439","n_code_links":1,"syntology":null},{"paper":null,"slug":"effect-of-random-histogram-equalization-on","title":"Effect of Random Histogram Equalization on Breast Calcification Analysis Using Deep Learning","date":"2022-05-03","arxiv_id":"2205.01684","n_code_links":0,"syntology":null},{"paper":"/paper/masked-generative-distillation","slug":"masked-generative-distillation","title":"Masked Generative Distillation","date":"2022-05-03","arxiv_id":"2205.01529","n_code_links":3,"syntology":null},{"paper":null,"slug":"spinenetv2-automated-detection-labelling-and","title":"SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans","date":"2022-05-03","arxiv_id":"2205.01683","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-accelerator-for-dilated-and","title":"Efficient Accelerator for Dilated and Transposed Convolution with Decomposition","date":"2022-05-02","arxiv_id":"2205.02103","n_code_links":0,"syntology":null},{"paper":"/paper/augmented-balanced-image-dataset-generator","slug":"augmented-balanced-image-dataset-generator","title":"Augmented Balanced Image Dataset Generator Using AugStatic Library","date":"2022-05-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"engineering-deep-learning-methods-on","title":"Engineering deep learning methods on automatic detection of damage in infrastructure due to extreme events","date":"2022-05-01","arxiv_id":"2205.02125","n_code_links":0,"syntology":null},{"paper":"/paper/improving-model-performance-and-removing-the","slug":"improving-model-performance-and-removing-the","title":"Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation","date":"2022-05-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"resnet18-model-with-sequential-layer-for","title":"Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset","date":"2022-05-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-mixed-domain-self-attention-network-for","title":"A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram","date":"2022-04-29","arxiv_id":"2204.13917","n_code_links":0,"syntology":null},{"paper":null,"slug":"birds-eye-view-measuring-behavior-and-posture","title":"Birds' Eye View: Measuring Behavior and Posture of Chickens as a Metric for Their Well-Being","date":"2022-04-29","arxiv_id":"2205.00069","n_code_links":0,"syntology":null},{"paper":"/paper/ossgan-open-set-semi-supervised-image","slug":"ossgan-open-set-semi-supervised-image","title":"OSSGAN: Open-Set Semi-Supervised Image Generation","date":"2022-04-29","arxiv_id":"2204.14249","n_code_links":1,"syntology":{"ran":10,"of":12,"n_ran_checked":3,"n_instrument":7,"unverified":2,"pointer_only":12,"phrase":"10 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; 7 where Syntology's instrument failed) · 2 unverified","official":{"repos":["raven38/ossgan"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"segmentation-of-kidney-stones-in-endoscopic","title":"Segmentation of kidney stones in endoscopic video feeds","date":"2022-04-29","arxiv_id":"2204.14175","n_code_links":0,"syntology":null},{"paper":"/paper/hpt-hierarchy-aware-prompt-tuning-for","slug":"hpt-hierarchy-aware-prompt-tuning-for","title":"HPT: Hierarchy-aware Prompt Tuning for Hierarchical Text Classification","date":"2022-04-28","arxiv_id":"2204.13413","n_code_links":1,"syntology":{"ran":2,"of":7,"n_ran_checked":2,"n_instrument":0,"unverified":5,"pointer_only":0,"phrase":"2 ran (of which 2 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) · 5 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["wzh9969/hpt"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":"/paper/unlocking-high-accuracy-differentially","slug":"unlocking-high-accuracy-differentially","title":"Unlocking High-Accuracy Differentially Private Image Classification through Scale","date":"2022-04-28","arxiv_id":"2204.13650","n_code_links":3,"syntology":null},{"paper":null,"slug":"boosting-adversarial-transferability-of-mlp","title":"Boosting Adversarial Transferability of MLP-Mixer","date":"2022-04-26","arxiv_id":"2204.12204","n_code_links":0,"syntology":null},{"paper":null,"slug":"correcting-motion-induced-fluorescence","title":"Correcting motion induced fluorescence artifacts in two-channel neural imaging","date":"2022-04-26","arxiv_id":"2204.12595","n_code_links":0,"syntology":null},{"paper":"/paper/rapq-rescuing-accuracy-for-power-of-two-low","slug":"rapq-rescuing-accuracy-for-power-of-two-low","title":"RAPQ: Rescuing Accuracy for Power-of-Two Low-bit Post-training Quantization","date":"2022-04-26","arxiv_id":"2204.12322","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["billamihom/rapq"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"u-net-with-resnet-backbone-for-garment","title":"U-Net with ResNet Backbone for Garment Landmarking Purpose","date":"2022-04-26","arxiv_id":"2204.12084","n_code_links":0,"syntology":null},{"paper":null,"slug":"unified-gcns-towards-connecting-gcns-with","title":"Unified GCNs: Towards Connecting GCNs with CNNs","date":"2022-04-26","arxiv_id":"2204.12300","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-hybrid-defense-method-against-adversarial","title":"A Hybrid Defense Method against Adversarial Attacks on Traffic Sign Classifiers in Autonomous Vehicles","date":"2022-04-25","arxiv_id":"2205.01225","n_code_links":0,"syntology":null},{"paper":null,"slug":"discriminative-feature-learning-framework","title":"Discriminative Feature Learning Framework with Gradient Preference for Anomaly Detection","date":"2022-04-23","arxiv_id":"2204.11014","n_code_links":0,"syntology":null},{"paper":null,"slug":"transformation-invariant-cancerous-tissue","title":"Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet","date":"2022-04-23","arxiv_id":"2204.11066","n_code_links":0,"syntology":null},{"paper":null,"slug":"balancing-expert-utilization-in-mixture-of","title":"Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability","date":"2022-04-22","arxiv_id":"2204.10598","n_code_links":0,"syntology":null},{"paper":"/paper/hrplanes-high-resolution-airplane-dataset-for","slug":"hrplanes-high-resolution-airplane-dataset-for","title":"A benchmark dataset for deep learning-based airplane detection: HRPlanes","date":"2022-04-22","arxiv_id":"2204.10959","n_code_links":1,"syntology":null},{"paper":null,"slug":"ai-based-automated-speech-therapy-tools-for","title":"AI-Based Automated Speech Therapy Tools for persons with Speech Sound Disorders: A Systematic Literature Review","date":"2022-04-21","arxiv_id":"2204.10325","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-neuron-coverage-needed-to-make-person","title":"Is Neuron Coverage Needed to Make Person Detection More Robust?","date":"2022-04-21","arxiv_id":"2204.10027","n_code_links":0,"syntology":null},{"paper":null,"slug":"audio-deep-fake-detection-system-with-neural","title":"Audio Deep Fake Detection System with Neural Stitching for ADD 2022","date":"2022-04-19","arxiv_id":"2204.08720","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-hate-speech-detection-from-bengali","slug":"multimodal-hate-speech-detection-from-bengali","title":"Multimodal Hate Speech Detection from Bengali Memes and Texts","date":"2022-04-19","arxiv_id":"2204.10196","n_code_links":1,"syntology":null},{"paper":"/paper/an-optimal-time-variable-learning-framework","slug":"an-optimal-time-variable-learning-framework","title":"An Optimal Time Variable Learning Framework for Deep Neural Networks","date":"2022-04-18","arxiv_id":"2204.08528","n_code_links":1,"syntology":null},{"paper":null,"slug":"application-of-transfer-learning-and-ensemble","title":"Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology","date":"2022-04-18","arxiv_id":"2204.08311","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-based-automatic-detection-of-2","title":"Deep Learning based Automatic Detection of Dicentric Chromosome","date":"2022-04-17","arxiv_id":"2204.08029","n_code_links":0,"syntology":null},{"paper":"/paper/auton-survival-an-open-source-package-for","slug":"auton-survival-an-open-source-package-for","title":"auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data","date":"2022-04-15","arxiv_id":"2204.07276","n_code_links":3,"syntology":null},{"paper":"/paper/conditional-injective-flows-for-bayesian","slug":"conditional-injective-flows-for-bayesian","title":"Conditional Injective Flows for Bayesian Imaging","date":"2022-04-15","arxiv_id":"2204.07664","n_code_links":1,"syntology":null},{"paper":"/paper/deepcsi-rethinking-wi-fi-radio-fingerprinting","slug":"deepcsi-rethinking-wi-fi-radio-fingerprinting","title":"DeepCSI: Rethinking Wi-Fi Radio Fingerprinting Through MU-MIMO CSI Feedback Deep Learning","date":"2022-04-15","arxiv_id":"2204.07614","n_code_links":1,"syntology":null},{"paper":null,"slug":"detecting-violence-in-video-based-on-deep","title":"Detecting Violence in Video Based on Deep Features Fusion Technique","date":"2022-04-15","arxiv_id":"2204.07443","n_code_links":0,"syntology":null},{"paper":null,"slug":"insta-bnn-binary-neural-network-with-instance","title":"INSTA-BNN: Binary Neural Network with INSTAnce-aware Threshold","date":"2022-04-15","arxiv_id":"2204.07439","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-environmental-sound-representation-to","title":"From Environmental Sound Representation to Robustness of 2D CNN Models Against Adversarial Attacks","date":"2022-04-14","arxiv_id":"2204.07018","n_code_links":0,"syntology":null},{"paper":null,"slug":"omnipd-one-step-person-detection-in-top-view","title":"OmniPD: One-Step Person Detection in Top-View Omnidirectional Indoor Scenes","date":"2022-04-14","arxiv_id":"2204.06846","n_code_links":0,"syntology":null},{"paper":null,"slug":"de-ireps-searching-for-improved-re","title":"Efficient Re-parameterization Operations Search for Easy-to-Deploy Network Based on Directional Evolutionary Strategy","date":"2022-04-13","arxiv_id":"2204.06403","n_code_links":0,"syntology":null},{"paper":"/paper/dmcnet-diversified-model-combination-network","slug":"dmcnet-diversified-model-combination-network","title":"DMCNet: Diversified Model Combination Network for Understanding Engagement from Video Screengrabs","date":"2022-04-13","arxiv_id":"2204.06454","n_code_links":1,"syntology":null},{"paper":null,"slug":"receding-neuron-importances-for-structured","title":"Receding Neuron Importances for Structured Pruning","date":"2022-04-13","arxiv_id":"2204.06404","n_code_links":0,"syntology":null},{"paper":"/paper/topformer-token-pyramid-transformer-for","slug":"topformer-token-pyramid-transformer-for","title":"TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation","date":"2022-04-12","arxiv_id":"2204.05525","n_code_links":3,"syntology":{"ran":2,"of":5,"n_ran_checked":2,"n_instrument":0,"unverified":3,"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) · 3 unverified","official":{"repos":["hustvl/TopFormer"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"dependable-intrusion-detection-system-for-iot","title":"Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach","date":"2022-04-11","arxiv_id":"2204.04837","n_code_links":0,"syntology":null},{"paper":"/paper/dilemma-self-supervised-shape-and-texture","slug":"dilemma-self-supervised-shape-and-texture","title":"Representation Learning by Detecting Incorrect Location Embeddings","date":"2022-04-10","arxiv_id":"2204.04788","n_code_links":1,"syntology":null},{"paper":"/paper/uncertainty-informed-deep-learning-models","slug":"uncertainty-informed-deep-learning-models","title":"Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology","date":"2022-04-09","arxiv_id":"2204.04516","n_code_links":2,"syntology":{"ran":9,"of":11,"n_ran_checked":9,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["jamesdolezal/biscuit","jamesdolezal/slideflow"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"multi-scale-temporal-network-for-continuous","title":"Multi-scale temporal network for continuous sign language recognition","date":"2022-04-08","arxiv_id":"2204.03864","n_code_links":0,"syntology":null},{"paper":"/paper/adapting-clip-for-phrase-localization-without","slug":"adapting-clip-for-phrase-localization-without","title":"Adapting CLIP For Phrase Localization Without Further Training","date":"2022-04-07","arxiv_id":"2204.03647","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":4,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["pals-ttic/adapting-clip"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"pneumonia-detection-in-chest-x-rays-using","title":"Pneumonia Detection in Chest X-Rays using Neural Networks","date":"2022-04-07","arxiv_id":"2204.03618","n_code_links":0,"syntology":null},{"paper":null,"slug":"swarm-behavior-tracking-based-on-a-deep","title":"Swarm behavior tracking based on a deep vision algorithm","date":"2022-04-07","arxiv_id":"2204.03319","n_code_links":0,"syntology":null},{"paper":"/paper/unified-contrastive-learning-in-image-text","slug":"unified-contrastive-learning-in-image-text","title":"Unified Contrastive Learning in Image-Text-Label Space","date":"2022-04-07","arxiv_id":"2204.03610","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":{"repos":["microsoft/unicl"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":null,"slug":"contextual-attention-mechanism-srgan-based","title":"Contextual Attention Mechanism, SRGAN Based Inpainting System for Eliminating Interruptions from Images","date":"2022-04-06","arxiv_id":"2204.02591","n_code_links":0,"syntology":null},{"paper":"/paper/efficientcellseg-efficient-volumetric-cell","slug":"efficientcellseg-efficient-volumetric-cell","title":"EfficientCellSeg: Efficient Volumetric Cell Segmentation Using Context Aware Pseudocoloring","date":"2022-04-06","arxiv_id":"2204.03014","n_code_links":1,"syntology":null},{"paper":null,"slug":"end-to-end-instance-edge-detection","title":"End-to-End Instance Edge Detection","date":"2022-04-06","arxiv_id":"2204.02898","n_code_links":0,"syntology":null},{"paper":"/paper/mixformer-mixing-features-across-windows-and","slug":"mixformer-mixing-features-across-windows-and","title":"MixFormer: Mixing Features across Windows and Dimensions","date":"2022-04-06","arxiv_id":"2204.02557","n_code_links":3,"syntology":{"ran":10,"of":14,"n_ran_checked":10,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"10 ran (of which 3 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) · 4 unverified","official":{"repos":["PaddlePaddle/PaddleClas"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"a-lightweight-and-accurate-yolo-like-network","title":"A lightweight and accurate YOLO-like network for small target detection in Aerial Imagery","date":"2022-04-05","arxiv_id":"2204.02325","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-cloud-based-phishing-attacks-by","title":"Detecting Cloud-Based Phishing Attacks by Combining Deep Learning Models","date":"2022-04-05","arxiv_id":"2204.02446","n_code_links":0,"syntology":null},{"paper":null,"slug":"explainable-deep-learning-algorithm-for","title":"Explainable Deep Learning Algorithm for Distinguishing Incomplete Kawasaki Disease by Coronary Artery Lesions on Echocardiographic Imaging","date":"2022-04-05","arxiv_id":"2204.02403","n_code_links":0,"syntology":null},{"paper":null,"slug":"when-sparsity-meets-dynamic-convolution","title":"SD-Conv: Towards the Parameter-Efficiency of Dynamic Convolution","date":"2022-04-05","arxiv_id":"2204.02227","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-mask-r-cnn-model-to-segment","title":"A Novel Mask R-CNN Model to Segment Heterogeneous Brain Tumors through Image Subtraction","date":"2022-04-04","arxiv_id":"2204.01201","n_code_links":0,"syntology":null},{"paper":"/paper/rediscovery-of-the-effectiveness-of-standard","slug":"rediscovery-of-the-effectiveness-of-standard","title":"EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection","date":"2022-04-04","arxiv_id":"2204.01209","n_code_links":1,"syntology":null},{"paper":"/paper/truck-axle-detection-with-convolutional","slug":"truck-axle-detection-with-convolutional","title":"Truck Axle Detection with Convolutional Neural Networks","date":"2022-04-04","arxiv_id":"2204.01868","n_code_links":1,"syntology":null},{"paper":"/paper/selective-kernel-attention-for-robust-speaker","slug":"selective-kernel-attention-for-robust-speaker","title":"Frequency and Multi-Scale Selective Kernel Attention for Speaker Verification","date":"2022-04-03","arxiv_id":"2204.01005","n_code_links":1,"syntology":null},{"paper":null,"slug":"constrained-sequence-to-tree-generation-for","title":"Constrained Sequence-to-Tree Generation for Hierarchical Text Classification","date":"2022-04-02","arxiv_id":"2204.00811","n_code_links":0,"syntology":null},{"paper":"/paper/triplenet-a-low-computing-power-platform-of","slug":"triplenet-a-low-computing-power-platform-of","title":"Efficient Convolutional Neural Networks on Raspberry Pi for Image Classification","date":"2022-04-02","arxiv_id":"2204.00943","n_code_links":1,"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":["RuiyangJu/TripleNet"],"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":null,"slug":"building-decision-forest-via-deep","title":"Building Decision Forest via Deep Reinforcement Learning","date":"2022-04-01","arxiv_id":"2204.00306","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-temporal-oriented-broadcast-resnet-for","title":"A Temporal-oriented Broadcast ResNet for COVID-19 Detection","date":"2022-03-31","arxiv_id":"2203.17012","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-classification-of-alzheimer-s","title":"Automatic Classification of Alzheimer's Disease using brain MRI data and deep Convolutional Neural Networks","date":"2022-03-31","arxiv_id":"2204.00068","n_code_links":0,"syntology":null},{"paper":"/paper/eend-ss-joint-end-to-end-neural-speaker","slug":"eend-ss-joint-end-to-end-neural-speaker","title":"EEND-SS: Joint End-to-End Neural Speaker Diarization and Speech Separation for Flexible Number of Speakers","date":"2022-03-31","arxiv_id":"2203.17068","n_code_links":1,"syntology":null},{"paper":"/paper/multi-granularity-alignment-domain-adaptation","slug":"multi-granularity-alignment-domain-adaptation","title":"Multi-Granularity Alignment Domain Adaptation for Object Detection","date":"2022-03-31","arxiv_id":"2203.16897","n_code_links":1,"syntology":null},{"paper":"/paper/underwater-single-channel-acoustic-signal","slug":"underwater-single-channel-acoustic-signal","title":"Underwater single-channel acoustic signal multitarget recognition using convolutional neural networks","date":"2022-03-31","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"universal-lymph-node-detection-in-t2-mri","title":"Universal Lymph Node Detection in T2 MRI using Neural Networks","date":"2022-03-31","arxiv_id":"2204.00622","n_code_links":0,"syntology":null},{"paper":"/paper/a-fuzzy-distance-based-ensemble-of-deep","slug":"a-fuzzy-distance-based-ensemble-of-deep","title":"A fuzzy distance-based ensemble of deep models for cervical cancer detection","date":"2022-03-30","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/an-efficient-anchor-free-universal-lesion","slug":"an-efficient-anchor-free-universal-lesion","title":"An Efficient Anchor-free Universal Lesion Detection in CT-scans","date":"2022-03-30","arxiv_id":"2203.16074","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-plain-vision-transformer-backbones","slug":"exploring-plain-vision-transformer-backbones","title":"Exploring Plain Vision Transformer Backbones for Object Detection","date":"2022-03-30","arxiv_id":"2203.16527","n_code_links":11,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"3 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; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["facebookresearch/detectron2"],"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/pp-yoloe-an-evolved-version-of-yolo","slug":"pp-yoloe-an-evolved-version-of-yolo","title":"PP-YOLOE: An evolved version of YOLO","date":"2022-03-30","arxiv_id":"2203.16250","n_code_links":8,"syntology":{"ran":22,"of":27,"n_ran_checked":21,"n_instrument":1,"unverified":5,"pointer_only":1,"phrase":"22 ran (of which 0 constructed an object rather than computing a result; 21 with no instrument failure: 2 honoured, 0 violated, 19 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","official":{"repos":["PaddlePaddle/PaddleDetection"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["listed","official"]}}}],"record_sha256":"3c88ec184b5bc4649fd0877ebc694ba7e8fbea4e6bcd27fa603793f39f15e0a4","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}