{"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/depthwise-separable-convolution/papers/5","list_of":"/method/depthwise-separable-convolution","method":"Depthwise Separable 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":5,"pages_in_order":12,"rows_per_page":100,"rows":[401,500],"of":1174,"counts":{"archive_papers_tagged":1174,"with_a_code_link":476,"where_syntology_ran_a_sample":118,"not_listed_spam_title":0,"listed":1174,"listed_where_code_ran":118,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":105,"every_run_a_failure_of_syntologys_instrument":13,"listed_with_a_run_with_no_instrument_failure":105,"listed_every_run_a_failure_of_syntologys_instrument":13,"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/depthwise-separable-convolution","prev":"/method/depthwise-separable-convolution/papers/4","next":"/method/depthwise-separable-convolution/papers/6","papers":[{"paper":null,"slug":"autosparse-towards-automated-sparse-training","title":"AUTOSPARSE: Towards Automated Sparse Training of Deep Neural Networks","date":"2023-04-14","arxiv_id":"2304.06941","n_code_links":0,"syntology":null},{"paper":"/paper/boosting-convolutional-neural-networks-with","slug":"boosting-convolutional-neural-networks-with","title":"Boosting Convolutional Neural Networks with Middle Spectrum Grouped Convolution","date":"2023-04-13","arxiv_id":"2304.06305","n_code_links":1,"syntology":null},{"paper":"/paper/deep-learning-approaches-to-osteosarcoma","slug":"deep-learning-approaches-to-osteosarcoma","title":"Deep Learning Approaches to Osteosarcoma Diagnosis and Classification: A Comparative Methodological Approach","date":"2023-04-13","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"ensemble-cnns-for-breast-tumor-classification","title":"Ensemble CNNs for Breast Tumor Classification","date":"2023-04-11","arxiv_id":"2304.13727","n_code_links":0,"syntology":null},{"paper":null,"slug":"lcdctcnn-lung-cancer-diagnosis-of-ct-scan","title":"LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model","date":"2023-04-10","arxiv_id":"2304.04814","n_code_links":0,"syntology":null},{"paper":null,"slug":"arithmetic-intensity-balancing-convolution","title":"Arithmetic Intensity Balancing Convolution for Hardware-aware Efficient Block Design","date":"2023-04-08","arxiv_id":"2304.04016","n_code_links":0,"syntology":null},{"paper":null,"slug":"surrogate-lagrangian-relaxation-a-path-to","title":"Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning","date":"2023-04-08","arxiv_id":"2304.04120","n_code_links":0,"syntology":null},{"paper":null,"slug":"local-rose-breeds-detection-system-using","title":"Local Rose Breeds Detection System Using Transfer Learning Techniques","date":"2023-04-07","arxiv_id":"2304.03509","n_code_links":0,"syntology":null},{"paper":null,"slug":"classification-of-skin-disease-using-transfer","title":"Classification of Skin Disease Using Transfer Learning in Convolutional Neural Networks","date":"2023-04-06","arxiv_id":"2304.02852","n_code_links":0,"syntology":null},{"paper":null,"slug":"spritz-ps-validation-of-synthetic-face-images","title":"Spritz-PS: Validation of Synthetic Face Images Using a Large Dataset of Printed Documents","date":"2023-04-06","arxiv_id":"2304.02982","n_code_links":0,"syntology":null},{"paper":null,"slug":"fishook-an-optimized-approach-to-marine","title":"FisHook -- An Optimized Approach to Marine Specie Classification using MobileNetV2","date":"2023-04-04","arxiv_id":"2304.01524","n_code_links":0,"syntology":null},{"paper":null,"slug":"galaxy-classification-using-transfer-learning","title":"Galaxy Classification Using Transfer Learning and Ensemble of CNNs With Multiple Colour Spaces","date":"2023-03-26","arxiv_id":"2305.00002","n_code_links":0,"syntology":null},{"paper":"/paper/fastvit-a-fast-hybrid-vision-transformer","slug":"fastvit-a-fast-hybrid-vision-transformer","title":"FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization","date":"2023-03-24","arxiv_id":"2303.14189","n_code_links":6,"syntology":{"ran":1,"of":5,"n_ran_checked":1,"n_instrument":0,"unverified":4,"pointer_only":5,"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) · 4 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["apple/ml-fastvit","rwightman/pytorch-image-models"],"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/magiceye-an-intelligent-wearable-towards","slug":"magiceye-an-intelligent-wearable-towards","title":"MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired","date":"2023-03-24","arxiv_id":"2303.13863","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-simple-and-generic-framework-for-feature","title":"A Simple and Generic Framework for Feature Distillation via Channel-wise Transformation","date":"2023-03-23","arxiv_id":"2303.13212","n_code_links":0,"syntology":null},{"paper":"/paper/scaneru-interactive-3d-visual-grounding-based","slug":"scaneru-interactive-3d-visual-grounding-based","title":"ScanERU: Interactive 3D Visual Grounding based on Embodied Reference Understanding","date":"2023-03-23","arxiv_id":"2303.13186","n_code_links":1,"syntology":null},{"paper":"/paper/reveal-to-revise-an-explainable-ai-life-cycle","slug":"reveal-to-revise-an-explainable-ai-life-cycle","title":"Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models","date":"2023-03-22","arxiv_id":"2303.12641","n_code_links":1,"syntology":null},{"paper":null,"slug":"bias-mitigation-techniques-in-image","title":"Bias mitigation techniques in image classification: fair machine learning in human heritage collections","date":"2023-03-20","arxiv_id":"2303.11449","n_code_links":0,"syntology":null},{"paper":"/paper/less-is-more-reducing-task-and-model","slug":"less-is-more-reducing-task-and-model","title":"Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation","date":"2023-03-20","arxiv_id":"2303.11203","n_code_links":1,"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":["l1997i/lim3d"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"artificial-intelligence-based-drone-for-early","title":"Artificial Intelligence based drone for early disease detection and precision pesticide management in cashew farming","date":"2023-03-15","arxiv_id":"2303.08556","n_code_links":0,"syntology":null},{"paper":"/paper/reinforce-data-multiply-impact-improved-model","slug":"reinforce-data-multiply-impact-improved-model","title":"Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement","date":"2023-03-15","arxiv_id":"2303.08983","n_code_links":1,"syntology":null},{"paper":"/paper/r-2-range-regularization-for-model","slug":"r-2-range-regularization-for-model","title":"R2 Loss: Range Restriction Loss for Model Compression and Quantization","date":"2023-03-14","arxiv_id":"2303.08253","n_code_links":0,"syntology":null},{"paper":null,"slug":"bag-of-tricks-with-quantized-convolutional","title":"Bag of Tricks with Quantized Convolutional Neural Networks for image classification","date":"2023-03-13","arxiv_id":"2303.07080","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-class-skin-cancer-classification","title":"Multi-class Skin Cancer Classification Architecture Based on Deep Convolutional Neural Network","date":"2023-03-13","arxiv_id":"2303.07520","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficienttempnet-temporal-super-resolution-of","title":"EfficientTempNet: Temporal Super-Resolution of Radar Rainfall","date":"2023-03-09","arxiv_id":"2303.05552","n_code_links":0,"syntology":null},{"paper":"/paper/hyt-nas-hybrid-transformers-neural","slug":"hyt-nas-hybrid-transformers-neural","title":"HyT-NAS: Hybrid Transformers Neural Architecture Search for Edge Devices","date":"2023-03-08","arxiv_id":"2303.04440","n_code_links":0,"syntology":null},{"paper":null,"slug":"psdnet-determination-of-particle-size","title":"PSDNet: Determination of Particle Size Distributions Using Synthetic Soil Images and Convolutional Neural Networks","date":"2023-03-07","arxiv_id":"2303.04269","n_code_links":0,"syntology":null},{"paper":null,"slug":"tinyad-memory-efficient-anomaly-detection-for","title":"TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT","date":"2023-03-07","arxiv_id":"2303.03611","n_code_links":0,"syntology":null},{"paper":null,"slug":"speeding-up-efficientnet-selecting-update","title":"Speeding Up EfficientNet: Selecting Update Blocks of Convolutional Neural Networks using Genetic Algorithm in Transfer Learning","date":"2023-03-01","arxiv_id":"2303.00261","n_code_links":0,"syntology":null},{"paper":"/paper/edge-computing-on-tpu-for-brain-implant","slug":"edge-computing-on-tpu-for-brain-implant","title":"Edge computing on TPU for brain implant signal analysis","date":"2023-02-28","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/learning-pairwise-interaction-for","slug":"learning-pairwise-interaction-for","title":"Learning Pairwise Interaction for Generalizable DeepFake Detection","date":"2023-02-26","arxiv_id":"2302.13288","n_code_links":1,"syntology":null},{"paper":null,"slug":"transferd2-automated-defect-detection","title":"TransferD2: Automated Defect Detection Approach in Smart Manufacturing using Transfer Learning Techniques","date":"2023-02-26","arxiv_id":"2302.13317","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-light-weight-deep-learning-model-for-remote","title":"A Light-weight Deep Learning Model for Remote Sensing Image Classification","date":"2023-02-25","arxiv_id":"2302.13028","n_code_links":0,"syntology":null},{"paper":"/paper/dermatological-diagnosis-explainability","slug":"dermatological-diagnosis-explainability","title":"Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks","date":"2023-02-23","arxiv_id":"2302.12084","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-general-purpose-transferable-predictor-for","title":"A General-Purpose Transferable Predictor for Neural Architecture Search","date":"2023-02-21","arxiv_id":"2302.10835","n_code_links":0,"syntology":null},{"paper":null,"slug":"time-to-embrace-natural-language-processing","title":"Time to Embrace Natural Language Processing (NLP)-based Digital Pathology: Benchmarking NLP- and Convolutional Neural Network-based Deep Learning Pipelines","date":"2023-02-21","arxiv_id":"2302.10406","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-incremental-gray-box-physical-adversarial","title":"An Incremental Gray-box Physical Adversarial Attack on Neural Network Training","date":"2023-02-20","arxiv_id":"2303.01245","n_code_links":0,"syntology":null},{"paper":"/paper/cfnet-cascade-fusion-network-for-dense","slug":"cfnet-cascade-fusion-network-for-dense","title":"CEDNet: A Cascade Encoder-Decoder Network for Dense Prediction","date":"2023-02-13","arxiv_id":"2302.06052","n_code_links":2,"syntology":{"ran":10,"of":12,"n_ran_checked":8,"n_instrument":2,"unverified":2,"pointer_only":12,"phrase":"10 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; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["zhanggang001/cednet","zhanggang001/cfnet"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/cholectriplet2022-show-me-a-tool-and-tell-me","slug":"cholectriplet2022-show-me-a-tool-and-tell-me","title":"CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection","date":"2023-02-13","arxiv_id":"2302.06294","n_code_links":2,"syntology":null},{"paper":null,"slug":"short-term-memory-convolutions","title":"Short-Term Memory Convolutions","date":"2023-02-08","arxiv_id":"2302.04331","n_code_links":0,"syntology":null},{"paper":null,"slug":"patch-gradient-descent-training-neural","title":"Patch Gradient Descent: Training Neural Networks on Very Large Images","date":"2023-01-31","arxiv_id":"2301.13817","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-latency-aware-cnn-depth-compression","slug":"efficient-latency-aware-cnn-depth-compression","title":"Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming","date":"2023-01-28","arxiv_id":"2301.12187","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["snu-mllab/efficient-cnn-depth-compression"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/rewarded-meta-pruning-meta-learning-with","slug":"rewarded-meta-pruning-meta-learning-with","title":"Rewarded meta-pruning: Meta Learning with Rewards for Channel Pruning","date":"2023-01-26","arxiv_id":"2301.11063","n_code_links":1,"syntology":null},{"paper":"/paper/model-soups-to-increase-inference-without","slug":"model-soups-to-increase-inference-without","title":"Model soups to increase inference without increasing compute time","date":"2023-01-24","arxiv_id":"2301.10092","n_code_links":1,"syntology":null},{"paper":null,"slug":"progressive-meta-pooling-learning-for","title":"Progressive Meta-Pooling Learning for Lightweight Image Classification Model","date":"2023-01-24","arxiv_id":"2301.10038","n_code_links":0,"syntology":null},{"paper":null,"slug":"computer-vision-for-a-camel-vehicle-collision","title":"Computer Vision for a Camel-Vehicle Collision Mitigation System","date":"2023-01-23","arxiv_id":"2301.09339","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-presentation-attack-detection-for","title":"Improving Presentation Attack Detection for ID Cards on Remote Verification Systems","date":"2023-01-23","arxiv_id":"2301.09542","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comparative-analysis-of-cnn-based","title":"A Comparative Analysis of CNN-Based Pretrained Models for the Detection and Prediction of Monkeypox","date":"2023-01-20","arxiv_id":"2302.10277","n_code_links":0,"syntology":null},{"paper":null,"slug":"pneumonia-detection-in-chest-x-ray-images","title":"Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance","date":"2023-01-20","arxiv_id":"2301.08479","n_code_links":0,"syntology":null},{"paper":"/paper/m3e-yolo-a-new-lightweight-network-for","slug":"m3e-yolo-a-new-lightweight-network-for","title":"M3E-Yolo: A New Lightweight Network for Traffic Sign Recognition","date":"2023-01-19","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/a-semi-trailer-truck-right-hook-turn-blind","slug":"a-semi-trailer-truck-right-hook-turn-blind","title":"Monocular Cyclist Detection with Convolutional Neural Networks","date":"2023-01-16","arxiv_id":"2303.11223","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-side-tuning-for-document","slug":"multimodal-side-tuning-for-document","title":"Multimodal Side-Tuning for Document Classification","date":"2023-01-16","arxiv_id":"2301.07502","n_code_links":1,"syntology":null},{"paper":null,"slug":"designing-an-improved-deep-learning-based","title":"Designing an Improved Deep Learning-based Model for COVID-19 Recognition in Chest X-ray Images: A Knowledge Distillation Approach","date":"2023-01-06","arxiv_id":"2301.02735","n_code_links":0,"syntology":null},{"paper":null,"slug":"lostnet-a-smart-way-for-lost-and-find","title":"LostNet: A smart way for lost and find","date":"2023-01-05","arxiv_id":"2301.02277","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-mobile-block-for-efficient-neural","slug":"rethinking-mobile-block-for-efficient-neural","title":"Rethinking Mobile Block for Efficient Attention-based Models","date":"2023-01-03","arxiv_id":"2301.01146","n_code_links":1,"syntology":null},{"paper":null,"slug":"bit-shrinking-limiting-instantaneous","title":"Bit-Shrinking: Limiting Instantaneous Sharpness for Improving Post-Training Quantization","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-dataset-and-a-deep-learning-method","title":"A Novel Dataset and a Deep Learning Method for Mitosis Nuclei Segmentation and Classification","date":"2022-12-27","arxiv_id":"2212.13401","n_code_links":0,"syntology":null},{"paper":null,"slug":"pruning-on-the-fly-a-recoverable-pruning","title":"Pruning On-the-Fly: A Recoverable Pruning Method without Fine-tuning","date":"2022-12-24","arxiv_id":"2212.12651","n_code_links":0,"syntology":null},{"paper":null,"slug":"cattle-detection-occlusion-problem","title":"Cattle Detection Occlusion Problem","date":"2022-12-21","arxiv_id":"2212.11418","n_code_links":0,"syntology":null},{"paper":null,"slug":"csmpq-class-separability-based-mixed","title":"CSMPQ:Class Separability Based Mixed-Precision Quantization","date":"2022-12-20","arxiv_id":"2212.10220","n_code_links":0,"syntology":null},{"paper":"/paper/from-xception-to-nexception-new-design","slug":"from-xception-to-nexception-new-design","title":"From Xception to NEXcepTion: New Design Decisions and Neural Architecture Search","date":"2022-12-16","arxiv_id":"2212.08448","n_code_links":1,"syntology":null},{"paper":"/paper/rethinking-vision-transformers-for-mobilenet","slug":"rethinking-vision-transformers-for-mobilenet","title":"Rethinking Vision Transformers for MobileNet Size and Speed","date":"2022-12-15","arxiv_id":"2212.08059","n_code_links":7,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["rwightman/pytorch-image-models","snap-research/efficientformer"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"paper":"/paper/establishing-a-stronger-baseline-for","slug":"establishing-a-stronger-baseline-for","title":"Establishing a stronger baseline for lightweight contrastive models","date":"2022-12-14","arxiv_id":"2212.07158","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-ensemble-method-to-automatically-grade","title":"An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images","date":"2022-12-12","arxiv_id":"2212.06265","n_code_links":0,"syntology":null},{"paper":"/paper/comparison-of-deep-object-detectors-on-a-new","slug":"comparison-of-deep-object-detectors-on-a-new","title":"Comparison Of Deep Object Detectors On A New Vulnerable Pedestrian Dataset","date":"2022-12-12","arxiv_id":"2212.06218","n_code_links":2,"syntology":null},{"paper":"/paper/an-ai-powered-vvpat-counter-for-elections-in","slug":"an-ai-powered-vvpat-counter-for-elections-in","title":"An AI-Powered VVPAT Counter for Elections in India","date":"2022-12-09","arxiv_id":"2212.11124","n_code_links":1,"syntology":null},{"paper":"/paper/slimmable-pruned-neural-networks","slug":"slimmable-pruned-neural-networks","title":"Slimmable Pruned Neural Networks","date":"2022-12-07","arxiv_id":"2212.03415","n_code_links":1,"syntology":null},{"paper":null,"slug":"mobiletl-on-device-transfer-learning-with","title":"MobileTL: On-device Transfer Learning with Inverted Residual Blocks","date":"2022-12-05","arxiv_id":"2212.03246","n_code_links":0,"syntology":null},{"paper":"/paper/lightweight-facial-attractiveness-prediction","slug":"lightweight-facial-attractiveness-prediction","title":"Lightweight Facial Attractiveness Prediction Using Dual Label Distribution","date":"2022-12-04","arxiv_id":"2212.01742","n_code_links":1,"syntology":null},{"paper":null,"slug":"resnet-structure-simplification-with-the","title":"ResNet Structure Simplification with the Convolutional Kernel Redundancy Measure","date":"2022-12-01","arxiv_id":"2212.00272","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-framework-for-decentralized-dynamic","title":"A Novel Framework for Decentralized Dynamic Resource Allocation Using Voronoi Tessellations","date":"2022-11-30","arxiv_id":"2212.00140","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimizing-explanations-by-network","title":"Optimizing Explanations by Network Canonization and Hyperparameter Search","date":"2022-11-30","arxiv_id":"2211.17174","n_code_links":0,"syntology":null},{"paper":"/paper/three-stage-binarization-of-color-document","slug":"three-stage-binarization-of-color-document","title":"Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks","date":"2022-11-29","arxiv_id":"2211.16098","n_code_links":1,"syntology":null},{"paper":null,"slug":"receptive-field-refinement-for-convolutional","title":"Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance","date":"2022-11-26","arxiv_id":"2211.14487","n_code_links":0,"syntology":null},{"paper":null,"slug":"mcffa-net-multi-contextual-feature-fusion-and","title":"MCFFA-Net: Multi-Contextual Feature Fusion and Attention Guided Network for Apple Foliar Disease Classification","date":"2022-11-25","arxiv_id":"2211.14175","n_code_links":0,"syntology":null},{"paper":"/paper/ghostnetv2-enhance-cheap-operation-with-long","slug":"ghostnetv2-enhance-cheap-operation-with-long","title":"GhostNetV2: Enhance Cheap Operation with Long-Range Attention","date":"2022-11-23","arxiv_id":"2211.12905","n_code_links":12,"syntology":{"ran":8,"of":10,"n_ran_checked":8,"n_instrument":0,"unverified":2,"pointer_only":10,"phrase":"8 ran (of which 7 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":null,"slug":"identification-of-surface-defects-on-solar-pv","title":"Identification of Surface Defects on Solar PV Panels and Wind Turbine Blades using Attention based Deep Learning Model","date":"2022-11-23","arxiv_id":"2211.15374","n_code_links":0,"syntology":null},{"paper":null,"slug":"classification-of-human-monkeypox-disease","title":"Classification of Human Monkeypox Disease Using Deep Learning Models and Attention Mechanisms","date":"2022-11-21","arxiv_id":"2211.15459","n_code_links":0,"syntology":null},{"paper":null,"slug":"intrusion-detection-in-internet-of-things","title":"Intrusion Detection in Internet of Things using Convolutional Neural Networks","date":"2022-11-18","arxiv_id":"2211.10062","n_code_links":0,"syntology":null},{"paper":null,"slug":"pruning-very-deep-neural-network-channels-for","title":"Pruning Very Deep Neural Network Channels for Efficient Inference","date":"2022-11-14","arxiv_id":"2211.08339","n_code_links":0,"syntology":null},{"paper":"/paper/exploiting-the-partly-scratch-off-lottery","slug":"exploiting-the-partly-scratch-off-lottery","title":"Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training","date":"2022-11-12","arxiv_id":"2211.08544","n_code_links":1,"syntology":null},{"paper":"/paper/repghost-a-hardware-efficient-ghost-module","slug":"repghost-a-hardware-efficient-ghost-module","title":"RepGhost: A Hardware-Efficient Ghost Module via Re-parameterization","date":"2022-11-11","arxiv_id":"2211.06088","n_code_links":3,"syntology":{"ran":10,"of":17,"n_ran_checked":10,"n_instrument":0,"unverified":7,"pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","official":{"repos":["chengpengchen/repghost","rwightman/pytorch-image-models"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":7,"ran_from_kinds":["official"]}}},{"paper":"/paper/efficient-large-scale-audio-tagging-via","slug":"efficient-large-scale-audio-tagging-via","title":"Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge Distillation","date":"2022-11-09","arxiv_id":"2211.04772","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["fschmid56/efficientat"],"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":"much-easier-said-than-done-falsifying-the","title":"Much Easier Said Than Done: Falsifying the Causal Relevance of Linear Decoding Methods","date":"2022-11-08","arxiv_id":"2211.04367","n_code_links":0,"syntology":null},{"paper":null,"slug":"neural-architectural-nonlinear-pre-processing","title":"Neural Architectural Nonlinear Pre-Processing for mmWave Radar-based Human Gesture Perception","date":"2022-11-07","arxiv_id":"2211.03502","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-robust-and-low-complexity-deep-learning","title":"A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Classification","date":"2022-11-05","arxiv_id":"2211.02820","n_code_links":0,"syntology":null},{"paper":null,"slug":"sleepywheels-an-ensemble-model-for-drowsiness","title":"SleepyWheels: An Ensemble Model for Drowsiness Detection leading to Accident Prevention","date":"2022-11-01","arxiv_id":"2211.00718","n_code_links":0,"syntology":null},{"paper":null,"slug":"transfer-learning-and-local-interpretable","title":"Transfer learning and Local interpretable model agnostic based visual approach in Monkeypox Disease Detection and Classification: A Deep Learning insights","date":"2022-11-01","arxiv_id":"2211.05633","n_code_links":0,"syntology":null},{"paper":"/paper/food-ingredients-recognition-through-multi-1","slug":"food-ingredients-recognition-through-multi-1","title":"Food Ingredients Recognition through Multi-label Learning","date":"2022-10-24","arxiv_id":"2210.14147","n_code_links":1,"syntology":null},{"paper":"/paper/perceptual-image-enhancement-for-smartphone","slug":"perceptual-image-enhancement-for-smartphone","title":"Perceptual Image Enhancement for Smartphone Real-Time Applications","date":"2022-10-24","arxiv_id":"2210.13552","n_code_links":1,"syntology":null},{"paper":"/paper/vitruvio-3d-building-meshes-via-single","slug":"vitruvio-3d-building-meshes-via-single","title":"Vitruvio: 3D Building Meshes via Single Perspective Sketches","date":"2022-10-24","arxiv_id":"2210.13634","n_code_links":1,"syntology":null},{"paper":"/paper/basq-branch-wise-activation-clipping-search","slug":"basq-branch-wise-activation-clipping-search","title":"BASQ: Branch-wise Activation-clipping Search Quantization for Sub-4-bit Neural Networks","date":"2022-10-23","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"robust-general-and-low-complexity-acoustic","title":"Robust, General, and Low Complexity Acoustic Scene Classification Systems and An Effective Visualization for Presenting a Sound Scene Context","date":"2022-10-16","arxiv_id":"2210.08610","n_code_links":0,"syntology":null},{"paper":null,"slug":"variant-parallelism-lightweight-deep","title":"Variant Parallelism: Lightweight Deep Convolutional Models for Distributed Inference on IoT Devices","date":"2022-10-15","arxiv_id":"2210.08376","n_code_links":0,"syntology":null},{"paper":null,"slug":"neural-network-compression-by-joint-sparsity","title":"Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction","date":"2022-10-14","arxiv_id":"2210.07451","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-model-compression-using-network","title":"Deep learning model compression using network sensitivity and gradients","date":"2022-10-11","arxiv_id":"2210.05111","n_code_links":0,"syntology":null},{"paper":"/paper/a-closer-look-at-hardware-friendly-weight","slug":"a-closer-look-at-hardware-friendly-weight","title":"A Closer Look at Hardware-Friendly Weight Quantization","date":"2022-10-07","arxiv_id":"2210.03671","n_code_links":1,"syntology":null},{"paper":"/paper/effective-self-supervised-pre-training-on-low","slug":"effective-self-supervised-pre-training-on-low","title":"Effective Self-supervised Pre-training on Low-compute Networks without Distillation","date":"2022-10-06","arxiv_id":"2210.02808","n_code_links":1,"syntology":{"ran":6,"of":9,"n_ran_checked":3,"n_instrument":3,"unverified":3,"pointer_only":3,"phrase":"6 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; 3 where Syntology's instrument failed) · 3 unverified","official":{"repos":["saic-fi/sslight"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"automated-medical-device-display-reading","title":"Automated Medical Device Display Reading Using Deep Learning Object Detection","date":"2022-10-04","arxiv_id":"2210.01325","n_code_links":0,"syntology":null},{"paper":null,"slug":"dare-a-large-scale-handwritten-date","title":"DARE: A large-scale handwritten date recognition system","date":"2022-10-02","arxiv_id":"2210.00503","n_code_links":0,"syntology":null}],"record_sha256":"602b44b3e9de8b1d03c88964d6a1f0e351de79d39977fdcb1dac9d6fdbefe26a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}