{"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/max-pooling/papers/27","list_of":"/method/max-pooling","method":"Max Pooling","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":27,"pages_in_order":72,"rows_per_page":100,"rows":[2601,2700],"of":7126,"counts":{"archive_papers_tagged":7126,"with_a_code_link":2898,"where_syntology_ran_a_sample":640,"not_listed_spam_title":0,"listed":7126,"listed_where_code_ran":640,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":531,"every_run_a_failure_of_syntologys_instrument":109,"listed_with_a_run_with_no_instrument_failure":531,"listed_every_run_a_failure_of_syntologys_instrument":109,"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/max-pooling","prev":"/method/max-pooling/papers/26","next":"/method/max-pooling/papers/28","papers":[{"paper":null,"slug":"adapting-pretrained-vision-language","title":"Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains","date":"2022-10-09","arxiv_id":"2210.04133","n_code_links":0,"syntology":null},{"paper":null,"slug":"sml-enhance-the-network-smoothness-with-skip","title":"SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction","date":"2022-10-09","arxiv_id":"2210.10725","n_code_links":0,"syntology":null},{"paper":null,"slug":"text-detection-and-recognition-based-on-a","title":"Text detection and recognition based on a lensless imaging system","date":"2022-10-09","arxiv_id":"2210.04244","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-deep-learning-network-with-differentiable","title":"A deep learning network with differentiable dynamic programming for retina OCT surface segmentation","date":"2022-10-08","arxiv_id":"2210.06335","n_code_links":0,"syntology":null},{"paper":null,"slug":"lw-isp-a-lightweight-model-with-isp-and-deep","title":"LW-ISP: A Lightweight Model with ISP and Deep Learning","date":"2022-10-08","arxiv_id":"2210.03904","n_code_links":0,"syntology":null},{"paper":"/paper/images-as-weight-matrices-sequential-image","slug":"images-as-weight-matrices-sequential-image","title":"Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules","date":"2022-10-07","arxiv_id":"2210.06184","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 2 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["idsia/fpainter"],"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":["official","unlocated"]}}},{"paper":"/paper/in-search-of-a-robust-facial-expressions","slug":"in-search-of-a-robust-facial-expressions","title":"In Search of a Robust Facial Expressions Recognition Model: A Large-Scale Visual Cross-Corpus Study","date":"2022-10-07","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/temporal-feature-alignment-in-contrastive","slug":"temporal-feature-alignment-in-contrastive","title":"Temporal Feature Alignment in Contrastive Self-Supervised Learning for Human Activity Recognition","date":"2022-10-07","arxiv_id":"2210.03382","n_code_links":1,"syntology":null},{"paper":"/paper/a-resnet-is-all-you-need-modeling-a-strong","slug":"a-resnet-is-all-you-need-modeling-a-strong","title":"A ResNet is All You Need? Modeling A Strong Baseline for Detecting Referable Diabetic Retinopathy in Fundus Images","date":"2022-10-06","arxiv_id":"2210.03180","n_code_links":1,"syntology":null},{"paper":null,"slug":"dual-stage-deeply-supervised-attention-based","title":"Dual-Stage Deeply Supervised Attention-based Convolutional Neural Networks for Mandibular Canal Segmentation in CBCT Scans","date":"2022-10-06","arxiv_id":"2210.03739","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-mixup-based-graph-learning-for","slug":"enhancing-mixup-based-graph-learning-for","title":"On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing","date":"2022-10-06","arxiv_id":"2210.03123","n_code_links":1,"syntology":null},{"paper":null,"slug":"advanced-deep-learning-architectures-for","title":"Advanced Deep Learning Architectures for Accurate Detection of Subsurface Tile Drainage Pipes from Remote Sensing Images","date":"2022-10-05","arxiv_id":"2210.02071","n_code_links":0,"syntology":null},{"paper":"/paper/bi-stride-multi-scale-graph-neural-network","slug":"bi-stride-multi-scale-graph-neural-network","title":"Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNN","date":"2022-10-05","arxiv_id":"2210.02573","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"0 ran · 2 unverified","official":{"repos":["eydcao/bsms-gnn"],"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/particle-clustering-in-turbulence-prediction","slug":"particle-clustering-in-turbulence-prediction","title":"Particle clustering in turbulence: Prediction of spatial and statistical properties with deep learning","date":"2022-10-05","arxiv_id":"2210.02339","n_code_links":1,"syntology":null},{"paper":null,"slug":"priornet-lesion-segmentation-in-pet-ct","title":"PriorNet: lesion segmentation in PET-CT including prior tumor appearance information","date":"2022-10-05","arxiv_id":"2210.02203","n_code_links":0,"syntology":null},{"paper":"/paper/analysis-of-the-performance-of-u-net-neural","slug":"analysis-of-the-performance-of-u-net-neural","title":"Analysis of the performance of U-Net neural networks for the segmentation of living cells","date":"2022-10-04","arxiv_id":"2210.01538","n_code_links":1,"syntology":null},{"paper":"/paper/gidn-a-lightweight-graph-inception-diffusion","slug":"gidn-a-lightweight-graph-inception-diffusion","title":"GIDN: A Lightweight Graph Inception Diffusion Network for High-efficient Link Prediction","date":"2022-10-04","arxiv_id":"2210.01301","n_code_links":0,"syntology":null},{"paper":null,"slug":"invariant-aggregator-for-defending-federated","title":"Invariant Aggregator for Defending against Federated Backdoor Attacks","date":"2022-10-04","arxiv_id":"2210.01834","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-flexible-inductive-bias-via","title":"Towards Flexible Inductive Bias via Progressive Reparameterization Scheduling","date":"2022-10-04","arxiv_id":"2210.01370","n_code_links":0,"syntology":null},{"paper":null,"slug":"feature-embedding-by-template-matching-as-a","title":"Feature Embedding by Template Matching as a ResNet Block","date":"2022-10-03","arxiv_id":"2210.00992","n_code_links":0,"syntology":null},{"paper":null,"slug":"multipod-convolutional-network","title":"Multipod Convolutional Network","date":"2022-10-03","arxiv_id":"2210.00689","n_code_links":0,"syntology":null},{"paper":"/paper/siamese-nas-using-trained-samples-efficiently","slug":"siamese-nas-using-trained-samples-efficiently","title":"Siamese-NAS: Using Trained Samples Efficiently to Find Lightweight Neural Architecture by Prior Knowledge","date":"2022-10-02","arxiv_id":"2210.00546","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-ensemble-of-convolutional-neural-networks-1","title":"An Ensemble of Convolutional Neural Networks to Detect Foliar Diseases in Apple Plants","date":"2022-10-01","arxiv_id":"2210.00298","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-augmented-convnext-unet-for-rectal","title":"Attention Augmented ConvNeXt UNet For Rectal Tumour Segmentation","date":"2022-10-01","arxiv_id":"2210.00227","n_code_links":0,"syntology":null},{"paper":null,"slug":"kernel-normalized-convolutional-networks-for","title":"Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning","date":"2022-09-30","arxiv_id":"2210.00053","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-skip-connection-model-as-a","slug":"rethinking-skip-connection-model-as-a","title":"Rethinking skip connection model as a learnable Markov chain","date":"2022-09-30","arxiv_id":"2209.15278","n_code_links":1,"syntology":null},{"paper":"/paper/towards-multi-spatiotemporal-scale","slug":"towards-multi-spatiotemporal-scale","title":"Towards Multi-spatiotemporal-scale Generalized PDE Modeling","date":"2022-09-30","arxiv_id":"2209.15616","n_code_links":2,"syntology":null},{"paper":null,"slug":"where-should-i-spend-my-flops-efficiency","title":"Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods","date":"2022-09-30","arxiv_id":"2209.15589","n_code_links":0,"syntology":null},{"paper":null,"slug":"creative-painting-with-latent-diffusion","title":"Creative Painting with Latent Diffusion Models","date":"2022-09-29","arxiv_id":"2209.14697","n_code_links":0,"syntology":null},{"paper":null,"slug":"eihi-net-out-of-distribution-generalization","title":"EiHi Net: Out-of-Distribution Generalization Paradigm","date":"2022-09-29","arxiv_id":"2209.14946","n_code_links":0,"syntology":null},{"paper":"/paper/facial-landmark-predictions-with-applications","slug":"facial-landmark-predictions-with-applications","title":"Facial Landmark Predictions with Applications to Metaverse","date":"2022-09-29","arxiv_id":"2209.14698","n_code_links":1,"syntology":null},{"paper":"/paper/make-a-video-text-to-video-generation-without","slug":"make-a-video-text-to-video-generation-without","title":"Make-A-Video: Text-to-Video Generation without Text-Video Data","date":"2022-09-29","arxiv_id":"2209.14792","n_code_links":2,"syntology":null},{"paper":null,"slug":"semantics-guided-object-removal-for-facial","title":"Semantics-Guided Object Removal for Facial Images: with Broad Applicability and Robust Style Preservation","date":"2022-09-29","arxiv_id":"2209.14479","n_code_links":0,"syntology":null},{"paper":null,"slug":"cssam-u-net-network-for-application-and","title":"Segmentation method of U-net sheet metal engineering drawing based on CBAM attention mechanism","date":"2022-09-28","arxiv_id":"2209.14102","n_code_links":0,"syntology":null},{"paper":null,"slug":"cyclegan-network-for-sheet-metal-welding","title":"Cyclegan Network for Sheet Metal Welding Drawing Translation","date":"2022-09-28","arxiv_id":"2209.14106","n_code_links":0,"syntology":null},{"paper":"/paper/recipro-cam-gradient-free-reciprocal-class","slug":"recipro-cam-gradient-free-reciprocal-class","title":"Recipro-CAM: Fast gradient-free visual explanations for convolutional neural networks","date":"2022-09-28","arxiv_id":"2209.14074","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-learning-based-detection-of-enlarged","title":"Deep Learning Based Detection of Enlarged Perivascular Spaces on Brain MRI","date":"2022-09-27","arxiv_id":"2209.13727","n_code_links":0,"syntology":null},{"paper":null,"slug":"measuring-overfitting-in-convolutional-neural","title":"Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise","date":"2022-09-27","arxiv_id":"2209.13382","n_code_links":0,"syntology":null},{"paper":null,"slug":"when-handcrafted-features-and-deep-features","title":"When Handcrafted Features and Deep Features Meet Mismatched Training and Test Sets for Deepfake Detection","date":"2022-09-27","arxiv_id":"2209.13289","n_code_links":0,"syntology":null},{"paper":"/paper/device-friendly-guava-fruit-and-leaf-disease","slug":"device-friendly-guava-fruit-and-leaf-disease","title":"Device-friendly Guava fruit and leaf disease detection using deep learning","date":"2022-09-26","arxiv_id":"2209.12557","n_code_links":1,"syntology":null},{"paper":null,"slug":"optical-neural-ordinary-differential","title":"Optical Neural Ordinary Differential Equations","date":"2022-09-26","arxiv_id":"2209.12898","n_code_links":0,"syntology":null},{"paper":"/paper/all-are-worth-words-a-vit-backbone-for-score","slug":"all-are-worth-words-a-vit-backbone-for-score","title":"All are Worth Words: A ViT Backbone for Diffusion Models","date":"2022-09-25","arxiv_id":"2209.12152","n_code_links":3,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":3,"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":{"repos":["baofff/U-ViT"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"development-of-ai-cloud-based-high","title":"Development of AI-cloud based high-sensitivity wireless smart sensor for port structure monitoring","date":"2022-09-24","arxiv_id":"2209.13646","n_code_links":0,"syntology":null},{"paper":"/paper/modular-degradation-simulation-and","slug":"modular-degradation-simulation-and","title":"Modular Degradation Simulation and Restoration for Under-Display Camera","date":"2022-09-23","arxiv_id":"2209.11455","n_code_links":1,"syntology":null},{"paper":"/paper/on-efficient-reinforcement-learning-for-full","slug":"on-efficient-reinforcement-learning-for-full","title":"On Efficient Reinforcement Learning for Full-length Game of StarCraft II","date":"2022-09-23","arxiv_id":"2209.11553","n_code_links":2,"syntology":{"ran":8,"of":10,"n_ran_checked":8,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["liuruoze/hiernet-sc2","liuruoze/mini-AlphaStar"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/rethinking-performance-gains-in-image","slug":"rethinking-performance-gains-in-image","title":"Rethinking Performance Gains in Image Dehazing Networks","date":"2022-09-23","arxiv_id":"2209.11448","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-kriston-ai-system-for-the-voxceleb","title":"The Kriston AI System for the VoxCeleb Speaker Recognition Challenge 2022","date":"2022-09-23","arxiv_id":"2209.11433","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-ct-based-airway-segmentation-using-u-2-net","title":"A CT-Based Airway Segmentation Using U$^2$-net Trained by the Dice Loss Function","date":"2022-09-22","arxiv_id":"2209.10796","n_code_links":0,"syntology":null},{"paper":"/paper/calving-fronts-and-where-to-find-them-a","slug":"calving-fronts-and-where-to-find-them-a","title":"Calving fronts and where to find them: a benchmark dataset and methodology for automatic glacier calving front extraction from synthetic aperture radar imagery","date":"2022-09-22","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"hierarchical-graph-convolutional-network","title":"Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity","date":"2022-09-22","arxiv_id":"2209.11232","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimization-of-fpga-based-cnn-accelerators","title":"Optimization of FPGA-based CNN Accelerators Using Metaheuristics","date":"2022-09-22","arxiv_id":"2209.11272","n_code_links":0,"syntology":null},{"paper":"/paper/sda-x-net-selective-depth-attention-networks","slug":"sda-x-net-selective-depth-attention-networks","title":"SDA-$x$Net: Selective Depth Attention Networks for Adaptive Multi-scale Feature Representation","date":"2022-09-21","arxiv_id":"2209.10327","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-trio-method-for-retinal-vessel-segmentation","title":"A Trio-Method for Retinal Vessel Segmentation using Image Processing","date":"2022-09-19","arxiv_id":"2209.11230","n_code_links":0,"syntology":null},{"paper":null,"slug":"effective-adaptation-in-multi-task-co","title":"Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving","date":"2022-09-19","arxiv_id":"2209.08953","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-approach-of-using-cnn-based","title":"Efficient approach of using CNN based pretrained model in Bangla handwritten digit recognition","date":"2022-09-19","arxiv_id":"2209.13005","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-shift-invariance-of-max-pooling","title":"On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networks","date":"2022-09-19","arxiv_id":"2209.11740","n_code_links":0,"syntology":null},{"paper":"/paper/energy-efficient-automatic-streetlight","slug":"energy-efficient-automatic-streetlight","title":"CNN based Intelligent Streetlight Management Using Smart CCTV Camera and Semantic Segmentation","date":"2022-09-18","arxiv_id":"2209.08633","n_code_links":1,"syntology":null},{"paper":null,"slug":"through-a-fair-looking-glass-mitigating-bias","title":"Through a fair looking-glass: mitigating bias in image datasets","date":"2022-09-18","arxiv_id":"2209.08648","n_code_links":0,"syntology":null},{"paper":"/paper/automated-segmentation-and-recurrence-risk","slug":"automated-segmentation-and-recurrence-risk","title":"Automated Segmentation and Recurrence Risk Prediction of Surgically Resected Lung Tumors with Adaptive Convolutional Neural Networks","date":"2022-09-17","arxiv_id":"2209.08423","n_code_links":1,"syntology":null},{"paper":null,"slug":"inducing-early-neural-collapse-in-deep-neural","title":"Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks","date":"2022-09-17","arxiv_id":"2209.08378","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-visual-interpretability-for","slug":"exploring-visual-interpretability-for","title":"Exploring Visual Interpretability for Contrastive Language-Image Pre-training","date":"2022-09-15","arxiv_id":"2209.07046","n_code_links":1,"syntology":null},{"paper":"/paper/improving-mitosis-detection-via-unet-based","slug":"improving-mitosis-detection-via-unet-based","title":"Improving Mitosis Detection Via UNet-based Adversarial Domain Homogenizer","date":"2022-09-15","arxiv_id":"2209.09193","n_code_links":1,"syntology":null},{"paper":"/paper/nu-net-an-unpretentious-nested-u-net-for","slug":"nu-net-an-unpretentious-nested-u-net-for","title":"Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation","date":"2022-09-15","arxiv_id":"2209.07193","n_code_links":2,"syntology":null},{"paper":null,"slug":"the-development-of-spatial-attention-u-net","title":"The Development of Spatial Attention U-Net for The Recovery of Ionospheric Measurements and The Extraction of Ionospheric Parameters","date":"2022-09-15","arxiv_id":"2209.07581","n_code_links":0,"syntology":null},{"paper":"/paper/label-refinement-network-from-synthetic-error","slug":"label-refinement-network-from-synthetic-error","title":"Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation","date":"2022-09-14","arxiv_id":"2209.06353","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-interplay-of-adversarial-robustness","title":"On the interplay of adversarial robustness and architecture components: patches, convolution and attention","date":"2022-09-14","arxiv_id":"2209.06953","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparative-analysis-of-segmentation-and","title":"Comparative analysis of segmentation and generative models for fingerprint retrieval task","date":"2022-09-13","arxiv_id":"2209.06172","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-training-on-multi-instance-gpus","title":"An Analysis of Collocation on GPUs for Deep Learning Training","date":"2022-09-13","arxiv_id":"2209.06018","n_code_links":0,"syntology":null},{"paper":null,"slug":"histoperm-a-permutation-based-view-generation","title":"HistoPerm: A Permutation-Based View Generation Approach for Improving Histopathologic Feature Representation Learning","date":"2022-09-13","arxiv_id":"2209.06185","n_code_links":0,"syntology":null},{"paper":"/paper/predicting-brain-multigraph-population-from-a","slug":"predicting-brain-multigraph-population-from-a","title":"Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification","date":"2022-09-13","arxiv_id":"2209.06005","n_code_links":1,"syntology":null},{"paper":"/paper/detecting-network-based-internet-censorship","slug":"detecting-network-based-internet-censorship","title":"Detecting Network-based Internet Censorship via Latent Feature Representation Learning","date":"2022-09-12","arxiv_id":"2209.05152","n_code_links":1,"syntology":null},{"paper":"/paper/git-re-basin-merging-models-modulo","slug":"git-re-basin-merging-models-modulo","title":"Git Re-Basin: Merging Models modulo Permutation Symmetries","date":"2022-09-11","arxiv_id":"2209.04836","n_code_links":3,"syntology":{"ran":6,"of":6,"n_ran_checked":1,"n_instrument":5,"unverified":0,"pointer_only":1,"phrase":"6 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; 5 where Syntology's instrument failed) · 0 unverified","official":{"repos":["samuela/git-re-basin"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"local-aware-global-attention-network-for","title":"Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images","date":"2022-09-11","arxiv_id":"2209.04821","n_code_links":0,"syntology":null},{"paper":null,"slug":"people-detection-and-social-distancing","title":"People detection and social distancing classification in smart cities for COVID-19 by using thermal images and deep learning algorithms","date":"2022-09-10","arxiv_id":"2209.04704","n_code_links":0,"syntology":null},{"paper":null,"slug":"in-situ-animal-behavior-classification-using","title":"In-situ animal behavior classification using knowledge distillation and fixed-point quantization","date":"2022-09-09","arxiv_id":"2209.04130","n_code_links":0,"syntology":null},{"paper":"/paper/retinal-image-restoration-and-vessel","slug":"retinal-image-restoration-and-vessel","title":"Retinal Image Restoration and Vessel Segmentation using Modified Cycle-CBAM and CBAM-UNet","date":"2022-09-09","arxiv_id":"2209.04234","n_code_links":2,"syntology":null},{"paper":null,"slug":"automatic-fetal-fat-quantification-from-mri","title":"Automatic fetal fat quantification from MRI","date":"2022-09-08","arxiv_id":"2209.03748","n_code_links":0,"syntology":null},{"paper":"/paper/context-recovery-and-knowledge-retrieval-a","slug":"context-recovery-and-knowledge-retrieval-a","title":"Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detection","date":"2022-09-07","arxiv_id":"2209.02899","n_code_links":1,"syntology":null},{"paper":"/paper/generative-adversarial-super-resolution-at","slug":"generative-adversarial-super-resolution-at","title":"Generative Adversarial Super-Resolution at the Edge with Knowledge Distillation","date":"2022-09-07","arxiv_id":"2209.03355","n_code_links":1,"syntology":null},{"paper":null,"slug":"plant-species-classification-using-transfer","title":"Plant Species Classification Using Transfer Learning by Pretrained Classifier VGG-19","date":"2022-09-07","arxiv_id":"2209.03076","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-masked-bounding-box-selection-based-resnet","title":"A Masked Bounding-Box Selection Based ResNet Predictor for Text Rotation Prediction","date":"2022-09-06","arxiv_id":"2209.09198","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-evaluation-of-u-net-in-renal-structure","title":"An evaluation of U-Net in Renal Structure Segmentation","date":"2022-09-06","arxiv_id":"2209.02247","n_code_links":0,"syntology":null},{"paper":null,"slug":"improved-sensor-based-animal-behavior","title":"Improved Sensor-Based Animal Behavior Classification Performance through Conditional Generative Adversarial Network","date":"2022-09-06","arxiv_id":"2209.03758","n_code_links":0,"syntology":null},{"paper":"/paper/macab-model-agnostic-clean-annotation","slug":"macab-model-agnostic-clean-annotation","title":"TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World","date":"2022-09-06","arxiv_id":"2209.02339","n_code_links":1,"syntology":null},{"paper":null,"slug":"multimodal-contrastive-learning-for-remote","title":"Multimodal contrastive learning for remote sensing tasks","date":"2022-09-06","arxiv_id":"2209.02329","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-outcome-of-the-2022-landslide4sense","title":"The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection from Multi-Source Satellite Imagery","date":"2022-09-06","arxiv_id":"2209.02556","n_code_links":0,"syntology":null},{"paper":"/paper/ensemble-of-pre-trained-neural-networks-for","slug":"ensemble-of-pre-trained-neural-networks-for","title":"Ensemble of Pre-Trained Neural Networks for Segmentation and Quality Detection of Transmission Electron Microscopy Images","date":"2022-09-05","arxiv_id":"2209.01908","n_code_links":1,"syntology":null},{"paper":"/paper/classification-of-breast-tumours-based-on","slug":"classification-of-breast-tumours-based-on","title":"Classification of Breast Tumours Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods","date":"2022-09-03","arxiv_id":"2209.01380","n_code_links":1,"syntology":null},{"paper":null,"slug":"autopet-challenge-combining-nn-unet-with-swin","title":"AutoPET Challenge: Combining nn-Unet with Swin UNETR Augmented by Maximum Intensity Projection Classifier","date":"2022-09-02","arxiv_id":"2209.01112","n_code_links":0,"syntology":null},{"paper":null,"slug":"detection-of-diabetic-retinopathy-using","title":"Detection of diabetic retinopathy using longitudinal self-supervised learning","date":"2022-09-02","arxiv_id":"2209.00915","n_code_links":0,"syntology":null},{"paper":null,"slug":"fast-fourier-convolution-based-remote-sensor","title":"Fast Fourier Convolution Based Remote Sensor Image Object Detection for Earth Observation","date":"2022-09-01","arxiv_id":"2209.00551","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-detection-of-morphing-attacks","title":"On the detection of morphing attacks generated by GANs","date":"2022-09-01","arxiv_id":"2209.00404","n_code_links":0,"syntology":null},{"paper":null,"slug":"physics-informed-mta-unet-prediction-of","title":"Physics-informed MTA-UNet: Prediction of Thermal Stress and Thermal Deformation of Satellites","date":"2022-09-01","arxiv_id":"2209.01009","n_code_links":0,"syntology":null},{"paper":null,"slug":"public-parking-spot-detection-and-geo","title":"Public Parking Spot Detection And Geo-localization Using Transfer Learning","date":"2022-09-01","arxiv_id":"2209.00213","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-identification-of-coal-and-rock","title":"Automatic Identification of Coal and Rock/Gangue Based on DenseNet and Gaussian Process","date":"2022-08-31","arxiv_id":"2208.14871","n_code_links":0,"syntology":null},{"paper":null,"slug":"intelligent-detect-for-substation-insulator","title":"Intelligent detect for substation insulator defects based on CenterMask","date":"2022-08-31","arxiv_id":"2208.14598","n_code_links":0,"syntology":null},{"paper":null,"slug":"segmentation-of-weakly-visible-environmental","title":"Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features","date":"2022-08-31","arxiv_id":"2208.14957","n_code_links":0,"syntology":null},{"paper":null,"slug":"swin-transformer-yolov5-for-real-time-wine","title":"Swin-transformer-yolov5 For Real-time Wine Grape Bunch Detection","date":"2022-08-30","arxiv_id":"2208.14508","n_code_links":0,"syntology":null},{"paper":"/paper/tcam-temporal-class-activation-maps-for","slug":"tcam-temporal-class-activation-maps-for","title":"TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos","date":"2022-08-30","arxiv_id":"2208.14542","n_code_links":1,"syntology":null},{"paper":null,"slug":"detection-and-classification-of-brain-tumors","title":"Detection and Classification of Brain tumors Using Deep Convolutional Neural Networks","date":"2022-08-28","arxiv_id":"2208.13264","n_code_links":0,"syntology":null}],"record_sha256":"98e985d4a914ad5db3afd107403de1cbd7cda1eb8ed9063627d13ea9726a0357","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}