{"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/kaiming-initialization/papers/2","list_of":"/method/kaiming-initialization","method":"Kaiming Initialization","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":2,"pages_in_order":30,"rows_per_page":100,"rows":[101,200],"of":2931,"counts":{"archive_papers_tagged":2931,"with_a_code_link":1332,"where_syntology_ran_a_sample":379,"not_listed_spam_title":0,"listed":2931,"listed_where_code_ran":379,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":319,"every_run_a_failure_of_syntologys_instrument":60,"listed_with_a_run_with_no_instrument_failure":319,"listed_every_run_a_failure_of_syntologys_instrument":60,"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/kaiming-initialization","prev":"/method/kaiming-initialization","next":"/method/kaiming-initialization/papers/3","papers":[{"paper":null,"slug":"deep-learning-powered-classification-of","title":"Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays","date":"2025-01-24","arxiv_id":"2501.14279","n_code_links":0,"syntology":null},{"paper":null,"slug":"relative-layer-wise-relevance-propagation-a","title":"Relative Layer-Wise Relevance Propagation: a more Robust Neural Networks eXplaination","date":"2025-01-24","arxiv_id":"2501.14322","n_code_links":0,"syntology":null},{"paper":"/paper/attribute-based-visual-reprogramming-for","slug":"attribute-based-visual-reprogramming-for","title":"Attribute-based Visual Reprogramming for Image Classification with CLIP","date":"2025-01-23","arxiv_id":"2501.13982","n_code_links":1,"syntology":null},{"paper":null,"slug":"one-cycle-structured-pruning-with-stability","title":"One-cycle Structured Pruning with Stability Driven Structure Search","date":"2025-01-23","arxiv_id":"2501.13439","n_code_links":0,"syntology":null},{"paper":"/paper/sparse-identification-of-nonlinear-dynamics-6","slug":"sparse-identification-of-nonlinear-dynamics-6","title":"Sparse identification of nonlinear dynamics and Koopman operators with Shallow Recurrent Decoder Networks","date":"2025-01-23","arxiv_id":"2501.13329","n_code_links":1,"syntology":null},{"paper":null,"slug":"robustness-of-selected-learning-models-under","title":"Robustness of Selected Learning Models under Label-Flipping Attack","date":"2025-01-21","arxiv_id":"2501.12516","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-multi-scale-feature-extraction-and-fusion","title":"A Multi-Scale Feature Extraction and Fusion Deep Learning Method for Classification of Wheat Diseases","date":"2025-01-17","arxiv_id":"2501.09938","n_code_links":0,"syntology":null},{"paper":"/paper/ai-driven-water-segmentation-with-deep","slug":"ai-driven-water-segmentation-with-deep","title":"AI Driven Water Segmentation with deep learning models for Enhanced Flood Monitoring","date":"2025-01-14","arxiv_id":"2501.08266","n_code_links":1,"syntology":null},{"paper":null,"slug":"decoding-interpretable-logic-rules-from","title":"Decoding Interpretable Logic Rules from Neural Networks","date":"2025-01-14","arxiv_id":"2501.08281","n_code_links":0,"syntology":null},{"paper":"/paper/bigger-isn-t-always-better-towards-a-general","slug":"bigger-isn-t-always-better-towards-a-general","title":"Bigger Isn't Always Better: Towards a General Prior for Medical Image Reconstruction","date":"2025-01-13","arxiv_id":"2501.07376","n_code_links":1,"syntology":null},{"paper":null,"slug":"synesthesia-of-machines-based-multi-modal","title":"Synesthesia of Machines Based Multi-Modal Intelligent V2V Channel Model","date":"2025-01-13","arxiv_id":"2501.07333","n_code_links":0,"syntology":null},{"paper":null,"slug":"natural-language-processing-and-deep-learning","title":"Natural Language Processing and Deep Learning Models to Classify Phase of Flight in Aviation Safety Occurrences","date":"2025-01-11","arxiv_id":"2501.06564","n_code_links":0,"syntology":null},{"paper":null,"slug":"topoformer-integrating-transformers-and","title":"TopoFormer: Integrating Transformers and ConvLSTMs for Coastal Topography Prediction","date":"2025-01-11","arxiv_id":"2501.06494","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparison-of-neural-models-for-x-ray-image","title":"Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection","date":"2025-01-08","arxiv_id":"2501.04196","n_code_links":0,"syntology":null},{"paper":null,"slug":"planarian-neural-networks-evolutionary","title":"Planarian Neural Networks: Evolutionary Patterns from Basic Bilateria Shaping Modern Artificial Neural Network Architectures","date":"2025-01-08","arxiv_id":"2501.04700","n_code_links":0,"syntology":null},{"paper":null,"slug":"radar-signal-recognition-through-self","title":"Radar Signal Recognition through Self-Supervised Learning and Domain Adaptation","date":"2025-01-07","arxiv_id":"2501.03461","n_code_links":0,"syntology":null},{"paper":null,"slug":"codevision-detecting-llm-generated-code-using","title":"CodeVision: Detecting LLM-Generated Code Using 2D Token Probability Maps and Vision Models","date":"2025-01-06","arxiv_id":"2501.03288","n_code_links":0,"syntology":null},{"paper":null,"slug":"scalable-forward-forward-algorithm","title":"Scalable Forward-Forward Algorithm","date":"2025-01-06","arxiv_id":"2501.03176","n_code_links":0,"syntology":null},{"paper":null,"slug":"pteenet-post-trained-early-exit-neural","title":"PTEENet: Post-Trained Early-Exit Neural Networks Augmentation for Inference Cost Optimization","date":"2025-01-05","arxiv_id":"2501.02508","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-head-explainer-a-general-framework-to","title":"Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers","date":"2025-01-02","arxiv_id":"2501.01311","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-focused-human-body-model-for-accurate","title":"A Focused Human Body Model for Accurate Anthropometric Measurements Extraction","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/foreground-covering-prototype-generation-and","slug":"foreground-covering-prototype-generation-and","title":"Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation","date":"2025-01-01","arxiv_id":"2501.00752","n_code_links":1,"syntology":null},{"paper":null,"slug":"pleas-merging-models-with-permutations-and-1","title":"PLeaS - Merging Models with Permutations and Least Squares","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-shape-guided-transformer-network-for","title":"A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images","date":"2024-12-31","arxiv_id":"2501.00360","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparative-analysis-of-2d-and-3d-resnet","title":"Comparative Analysis of 2D and 3D ResNet Architectures for IDH and MGMT Mutation Detection in Glioma Patients","date":"2024-12-30","arxiv_id":"2412.21091","n_code_links":0,"syntology":null},{"paper":null,"slug":"residual-connection-networks-in-medical-image","title":"Residual Connection Networks in Medical Image Processing: Exploration of ResUnet++ Model Driven by Human Computer Interaction","date":"2024-12-30","arxiv_id":"2412.20709","n_code_links":0,"syntology":null},{"paper":"/paper/mgan-crcm-a-novel-multiple-generative","slug":"mgan-crcm-a-novel-multiple-generative","title":"MGAN-CRCM: A Novel Multiple Generative Adversarial Network and Coarse-Refinement Based Cognizant Method for Image Inpainting","date":"2024-12-25","arxiv_id":"2412.19000","n_code_links":1,"syntology":null},{"paper":null,"slug":"autosculpt-a-pattern-based-model-auto-pruning","title":"AutoSculpt: A Pattern-based Model Auto-pruning Framework Using Reinforcement Learning and Graph Learning","date":"2024-12-24","arxiv_id":"2412.18091","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-intrinsically-explainable-approach-to","title":"An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling","date":"2024-12-23","arxiv_id":"2412.17258","n_code_links":0,"syntology":null},{"paper":null,"slug":"collaborative-optimization-in-financial-data","title":"Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt","date":"2024-12-23","arxiv_id":"2412.17314","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-contrastive-learning-inspired-by","slug":"enhancing-contrastive-learning-inspired-by","title":"Enhancing Contrastive Learning Inspired by the Philosophy of \"The Blind Men and the Elephant\"","date":"2024-12-21","arxiv_id":"2412.16522","n_code_links":1,"syntology":null},{"paper":null,"slug":"sensitive-image-classification-by-vision","title":"Sensitive Image Classification by Vision Transformers","date":"2024-12-21","arxiv_id":"2412.16446","n_code_links":0,"syntology":null},{"paper":null,"slug":"seagrassfinder-deep-learning-for-eelgrass","title":"SeagrassFinder: Deep Learning for Eelgrass Detection and Coverage Estimation in the Wild","date":"2024-12-20","arxiv_id":"2412.16147","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-supervised-radiograph-anatomical-region","title":"Self-Supervised Radiograph Anatomical Region Classification -- How Clean Is Your Real-World Data?","date":"2024-12-20","arxiv_id":"2412.15967","n_code_links":0,"syntology":null},{"paper":null,"slug":"maximising-histopathology-segmentation-using","title":"Maximising Histopathology Segmentation using Minimal Labels via Self-Supervision","date":"2024-12-19","arxiv_id":"2412.15389","n_code_links":0,"syntology":null},{"paper":null,"slug":"mitraclip-device-automated-localization-in-3d","title":"MitraClip Device Automated Localization in 3D Transesophageal Echocardiography via Deep Learning","date":"2024-12-19","arxiv_id":"2412.15013","n_code_links":0,"syntology":null},{"paper":"/paper/explicit-and-implicit-graduated-optimization","slug":"explicit-and-implicit-graduated-optimization","title":"Explicit and Implicit Graduated Optimization in Deep Neural Networks","date":"2024-12-16","arxiv_id":"2412.11501","n_code_links":1,"syntology":null},{"paper":null,"slug":"samic-segment-anything-with-in-context","title":"SAMIC: Segment Anything with In-Context Spatial Prompt Engineering","date":"2024-12-16","arxiv_id":"2412.11998","n_code_links":0,"syntology":null},{"paper":null,"slug":"global-estimation-of-subsurface-eddy-kinetic","title":"Global Estimation of Subsurface Eddy Kinetic Energy of Mesoscale Eddies Using a Multiple-input Residual Neural Network","date":"2024-12-14","arxiv_id":"2412.10656","n_code_links":0,"syntology":null},{"paper":null,"slug":"understand-the-effectiveness-of-shortcuts","title":"Understand the Effectiveness of Shortcuts through the Lens of DCA","date":"2024-12-13","arxiv_id":"2412.09853","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-efficient-framework-for-enhancing","title":"An Efficient Framework for Enhancing Discriminative Models via Diffusion Techniques","date":"2024-12-12","arxiv_id":"2412.09063","n_code_links":0,"syntology":null},{"paper":null,"slug":"embeddings-are-all-you-need-achieving-high","title":"Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis","date":"2024-12-12","arxiv_id":"2412.09445","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-stage-segmentation-and-cascade","title":"Multi-Stage Segmentation and Cascade Classification Methods for Improving Cardiac MRI Analysis","date":"2024-12-12","arxiv_id":"2412.09386","n_code_links":0,"syntology":null},{"paper":null,"slug":"stochastic-learning-of-non-conjugate","title":"Stochastic Learning of Non-Conjugate Variational Posterior for Image Classification","date":"2024-12-12","arxiv_id":"2412.08951","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-gravitational-wave-parameter","title":"Efficient Gravitational Wave Parameter Estimation via Knowledge Distillation: A ResNet1D-IAF Approach","date":"2024-12-11","arxiv_id":"2412.08672","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-multimodal-ensemble-approach-for-clear-cell","title":"A multimodal ensemble approach for clear cell renal cell carcinoma treatment outcome prediction","date":"2024-12-10","arxiv_id":"2412.07136","n_code_links":0,"syntology":null},{"paper":null,"slug":"adaptive-epsilon-adversarial-training-for","title":"Adaptive Epsilon Adversarial Training for Robust Gravitational Wave Parameter Estimation Using Normalizing Flows","date":"2024-12-10","arxiv_id":"2412.07559","n_code_links":0,"syntology":null},{"paper":"/paper/amclr-unified-augmented-learning-for-cross","slug":"amclr-unified-augmented-learning-for-cross","title":"AmCLR: Unified Augmented Learning for Cross-Modal Representations","date":"2024-12-10","arxiv_id":"2412.07979","n_code_links":1,"syntology":null},{"paper":null,"slug":"dense-cross-connected-ensemble-convolutional","title":"Dense Cross-Connected Ensemble Convolutional Neural Networks for Enhanced Model Robustness","date":"2024-12-09","arxiv_id":"2412.07022","n_code_links":0,"syntology":null},{"paper":null,"slug":"thermal-image-based-fault-diagnosis-in","title":"Thermal Image-based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks","date":"2024-12-08","arxiv_id":"2412.05901","n_code_links":0,"syntology":null},{"paper":"/paper/colonnet-a-hybrid-of-densenet121-and-u-net","slug":"colonnet-a-hybrid-of-densenet121-and-u-net","title":"ColonNet: A Hybrid Of DenseNet121 And U-NET Model For Detection And Segmentation Of GI Bleeding","date":"2024-12-06","arxiv_id":"2412.05216","n_code_links":1,"syntology":null},{"paper":"/paper/machine-learning-based-mmwave-mimo-beam","slug":"machine-learning-based-mmwave-mimo-beam","title":"Machine Learning-Based mmWave MIMO Beam Tracking in V2I Scenarios: Algorithms and Datasets","date":"2024-12-06","arxiv_id":"2412.05427","n_code_links":1,"syntology":null},{"paper":null,"slug":"mitigating-instance-dependent-label-noise","title":"Mitigating Instance-Dependent Label Noise: Integrating Self-Supervised Pretraining with Pseudo-Label Refinement","date":"2024-12-06","arxiv_id":"2412.04898","n_code_links":0,"syntology":null},{"paper":null,"slug":"multimodal-sentiment-analysis-based-on-bert","title":"Multimodal Sentiment Analysis Based on BERT and ResNet","date":"2024-12-04","arxiv_id":"2412.03625","n_code_links":0,"syntology":null},{"paper":"/paper/tight-pac-bayesian-risk-certificates-for","slug":"tight-pac-bayesian-risk-certificates-for","title":"Tight PAC-Bayesian Risk Certificates for Contrastive Learning","date":"2024-12-04","arxiv_id":"2412.03486","n_code_links":1,"syntology":null},{"paper":"/paper/vision-transformers-for-weakly-supervised","slug":"vision-transformers-for-weakly-supervised","title":"Vision Transformers for Weakly-Supervised Microorganism Enumeration","date":"2024-12-03","arxiv_id":"2412.02250","n_code_links":2,"syntology":null},{"paper":null,"slug":"explorations-in-self-supervised-learning","title":"Explorations in Self-Supervised Learning: Dataset Composition Testing for Object Classification","date":"2024-12-01","arxiv_id":"2412.00770","n_code_links":0,"syntology":null},{"paper":null,"slug":"pairwise-discernment-of-affectnet-expressions","title":"Pairwise Discernment of AffectNet Expressions with ArcFace","date":"2024-12-01","arxiv_id":"2412.01860","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-privacy-preserving-medical-imaging","title":"Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture","date":"2024-12-01","arxiv_id":"2412.00687","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-skin-cancer-diagnosis-scd-using","slug":"enhancing-skin-cancer-diagnosis-scd-using","title":"Enhancing Skin Cancer Diagnosis (SCD) Using Late Discrete Wavelet Transform (DWT) and New Swarm-Based Optimizers","date":"2024-11-30","arxiv_id":"2412.00472","n_code_links":1,"syntology":null},{"paper":null,"slug":"ikun-initialization-to-keep-snn-training-and","title":"IKUN: Initialization to Keep snn training and generalization great with sUrrogate-stable variaNce","date":"2024-11-27","arxiv_id":"2411.18250","n_code_links":0,"syntology":null},{"paper":null,"slug":"mortality-prediction-of-pulmonary-embolism","title":"Mortality Prediction of Pulmonary Embolism Patients with Deep Learning and XGBoost","date":"2024-11-27","arxiv_id":"2411.18063","n_code_links":0,"syntology":null},{"paper":null,"slug":"addressing-vulnerabilities-in-ai-image","title":"Addressing Vulnerabilities in AI-Image Detection: Challenges and Proposed Solutions","date":"2024-11-26","arxiv_id":"2412.00073","n_code_links":0,"syntology":null},{"paper":null,"slug":"explainable-ai-approach-using-near-misses","title":"Explainable AI Approach using Near Misses Analysis","date":"2024-11-25","arxiv_id":"2411.16895","n_code_links":0,"syntology":null},{"paper":"/paper/medical-slice-transformer-improved-diagnosis","slug":"medical-slice-transformer-improved-diagnosis","title":"Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2","date":"2024-11-24","arxiv_id":"2411.15802","n_code_links":1,"syntology":null},{"paper":"/paper/munba-machine-unlearning-via-nash-bargaining","slug":"munba-machine-unlearning-via-nash-bargaining","title":"MUNBa: Machine Unlearning via Nash Bargaining","date":"2024-11-23","arxiv_id":"2411.15537","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":4,"n_instrument":1,"unverified":0,"pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 2 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["JingWu321/MUNBa"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"pushing-the-limits-of-sparsity-a-bag-of","title":"Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning","date":"2024-11-20","arxiv_id":"2411.13545","n_code_links":0,"syntology":null},{"paper":"/paper/dlbacktrace-a-model-agnostic-explainability","slug":"dlbacktrace-a-model-agnostic-explainability","title":"DLBacktrace: A Model Agnostic Explainability for any Deep Learning Models","date":"2024-11-19","arxiv_id":"2411.12643","n_code_links":1,"syntology":null},{"paper":null,"slug":"faster-multi-gpu-training-with-ppll-a","title":"Faster Multi-GPU Training with PPLL: A Pipeline Parallelism Framework Leveraging Local Learning","date":"2024-11-19","arxiv_id":"2411.12780","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-supervised-learning-in-deep-networks-a","title":"Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification","date":"2024-11-19","arxiv_id":"2411.12151","n_code_links":0,"syntology":null},{"paper":null,"slug":"fert-real-time-facial-expression-recognition","title":"FERT: Real-Time Facial Expression Recognition with Short-Range FMCW Radar","date":"2024-11-18","arxiv_id":"2411.11619","n_code_links":0,"syntology":null},{"paper":null,"slug":"lung-disease-detection-with-vision","title":"Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods","date":"2024-11-18","arxiv_id":"2411.11376","n_code_links":0,"syntology":null},{"paper":"/paper/deep-feature-response-discriminative","slug":"deep-feature-response-discriminative","title":"Deep Feature Response Discriminative Calibration","date":"2024-11-16","arxiv_id":"2411.13582","n_code_links":1,"syntology":null},{"paper":null,"slug":"adaptive-physics-guided-neural-network","title":"Adaptive Physics-Guided Neural Network","date":"2024-11-15","arxiv_id":"2411.10064","n_code_links":0,"syntology":null},{"paper":null,"slug":"fedcl-ensemble-learning-a-framework-of","title":"FedCL-Ensemble Learning: A Framework of Federated Continual Learning with Ensemble Transfer Learning Enhanced for Alzheimer's MRI Classifications while Preserving Privacy","date":"2024-11-15","arxiv_id":"2411.12756","n_code_links":0,"syntology":null},{"paper":null,"slug":"complexity-aware-training-of-deep-neural","title":"Complexity-Aware Training of Deep Neural Networks for Optimal Structure Discovery","date":"2024-11-14","arxiv_id":"2411.09127","n_code_links":0,"syntology":null},{"paper":null,"slug":"artistic-neural-style-transfer-algorithms","title":"Artistic Neural Style Transfer Algorithms with Activation Smoothing","date":"2024-11-12","arxiv_id":"2411.08014","n_code_links":0,"syntology":null},{"paper":"/paper/rl-pruner-structured-pruning-using","slug":"rl-pruner-structured-pruning-using","title":"RL-Pruner: Structured Pruning Using Reinforcement Learning for CNN Compression and Acceleration","date":"2024-11-10","arxiv_id":"2411.06463","n_code_links":1,"syntology":null},{"paper":null,"slug":"breaking-the-ice-video-segmentation-for-close","title":"Breaking The Ice: Video Segmentation for Close-Range Ice-Covered Waters","date":"2024-11-07","arxiv_id":"2411.05225","n_code_links":0,"syntology":null},{"paper":"/paper/prion-vit-prions-inspired-vision-transformers","slug":"prion-vit-prions-inspired-vision-transformers","title":"Prion-ViT: Prions-Inspired Vision Transformers for Temperature prediction with Specklegrams","date":"2024-11-06","arxiv_id":"2411.05836","n_code_links":0,"syntology":null},{"paper":"/paper/specialized-foundation-models-struggle-to","slug":"specialized-foundation-models-struggle-to","title":"Specialized Foundation Models Struggle to Beat Supervised Baselines","date":"2024-11-05","arxiv_id":"2411.02796","n_code_links":2,"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: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["Zongzhe-Xu/AutoAR","ritvikgupta199/DASHA"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"efficient-medical-image-retrieval-using","title":"Efficient Medical Image Retrieval Using DenseNet and FAISS for BIRADS Classification","date":"2024-11-03","arxiv_id":"2411.01473","n_code_links":0,"syntology":null},{"paper":"/paper/few-class-arena-a-benchmark-for-efficient","slug":"few-class-arena-a-benchmark-for-efficient","title":"Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement","date":"2024-11-02","arxiv_id":"2411.01099","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluation-metric-for-quality-control-and","title":"Evaluation Metric for Quality Control and Generative Models in Histopathology Images","date":"2024-11-01","arxiv_id":"2411.01034","n_code_links":0,"syntology":null},{"paper":null,"slug":"reducing-oversmoothing-through-informed","title":"Reducing Oversmoothing through Informed Weight Initialization in Graph Neural Networks","date":"2024-10-31","arxiv_id":"2410.23830","n_code_links":0,"syntology":null},{"paper":null,"slug":"loflat-local-feature-matching-using-focused","title":"LoFLAT: Local Feature Matching using Focused Linear Attention Transformer","date":"2024-10-30","arxiv_id":"2410.22710","n_code_links":0,"syntology":null},{"paper":null,"slug":"nested-resnet-a-vision-based-method-for","title":"Nested ResNet: A Vision-Based Method for Detecting the Sensing Area of a Drop-in Gamma Probe","date":"2024-10-30","arxiv_id":"2410.23154","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-driving-car-racing-application-of-deep","title":"Self-Driving Car Racing: Application of Deep Reinforcement Learning","date":"2024-10-30","arxiv_id":"2410.22766","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficientnet-with-hybrid-attention-mechanisms","title":"Breast Cancer Histopathology Classification using CBAM-EfficientNetV2 with Transfer Learning","date":"2024-10-29","arxiv_id":"2410.22392","n_code_links":0,"syntology":null},{"paper":"/paper/multimodality-helps-few-shot-3d-point-cloud","slug":"multimodality-helps-few-shot-3d-point-cloud","title":"Multimodality Helps Few-Shot 3D Point Cloud Semantic Segmentation","date":"2024-10-29","arxiv_id":"2410.22489","n_code_links":2,"syntology":{"ran":0,"of":3,"n_ran_checked":0,"n_instrument":0,"unverified":3,"pointer_only":3,"phrase":"0 ran · 3 unverified","official":{"repos":["zhaochongan/multimodality-3d-few-shot"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"paper":"/paper/breccia-and-basalt-classification-of-thin","slug":"breccia-and-basalt-classification-of-thin","title":"Breccia and basalt classification of thin sections of Apollo rocks with deep learning","date":"2024-10-28","arxiv_id":"2410.21024","n_code_links":1,"syntology":null},{"paper":null,"slug":"accelerating-augmentation-invariance","title":"Accelerating Augmentation Invariance Pretraining","date":"2024-10-27","arxiv_id":"2410.22364","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-approach-to-hummed-tune-and-song-sequences","title":"An approach to hummed-tune and song sequences matching","date":"2024-10-27","arxiv_id":"2410.20352","n_code_links":0,"syntology":null},{"paper":null,"slug":"high-quality-ecg-dataset-based-on-mit-bih","title":"High quality ECG dataset based on MIT-BIH recordings for improved heartbeats classification","date":"2024-10-27","arxiv_id":"2411.07252","n_code_links":0,"syntology":null},{"paper":null,"slug":"complexity-matters-effective-dimensionality","title":"Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness","date":"2024-10-24","arxiv_id":"2410.18556","n_code_links":0,"syntology":null},{"paper":null,"slug":"integrating-deep-feature-extraction-and","title":"Integrating Deep Feature Extraction and Hybrid ResNet-DenseNet Model for Multi-Class Abnormality Detection in Endoscopic Images","date":"2024-10-24","arxiv_id":"2410.18457","n_code_links":0,"syntology":null},{"paper":null,"slug":"calibrating-deep-neural-network-using","title":"Calibrating Deep Neural Network using Euclidean Distance","date":"2024-10-23","arxiv_id":"2410.18321","n_code_links":0,"syntology":null},{"paper":null,"slug":"emotion-recognition-with-facial-attention-and","title":"Emotion Recognition with Facial Attention and Objective Activation Functions","date":"2024-10-23","arxiv_id":"2410.17740","n_code_links":0,"syntology":null},{"paper":null,"slug":"rethinking-positive-pairs-in-contrastive","title":"Rethinking Positive Pairs in Contrastive Learning","date":"2024-10-23","arxiv_id":"2410.18200","n_code_links":0,"syntology":null},{"paper":null,"slug":"sigclr-sigmoid-contrastive-learning-of-visual","title":"SigCLR: Sigmoid Contrastive Learning of Visual Representations","date":"2024-10-22","arxiv_id":"2410.17427","n_code_links":0,"syntology":null}],"record_sha256":"68cab6cdf4f76c874d65fdd2b84d3827848d2500d429a4e221a20802438a6302","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}