{"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/4","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":4,"pages_in_order":72,"rows_per_page":100,"rows":[301,400],"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/3","next":"/method/max-pooling/papers/5","papers":[{"paper":"/paper/sturm-flood-a-curated-dataset-for-deep","slug":"sturm-flood-a-curated-dataset-for-deep","title":"STURM-Flood: a curated dataset for deep learning-based flood extent mapping leveraging Sentinel-1 and Sentinel-2 imagery","date":"2025-02-06","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"synthetic-poisoning-attacks-the-impact-of","title":"Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation","date":"2025-02-06","arxiv_id":"2502.03825","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-fair-and-robust-face-parsing-for","title":"Towards Fair and Robust Face Parsing for Generative AI: A Multi-Objective Approach","date":"2025-02-06","arxiv_id":"2502.04391","n_code_links":0,"syntology":null},{"paper":null,"slug":"vision-integrated-llms-for-autonomous-driving","title":"Vision-Integrated LLMs for Autonomous Driving Assistance : Human Performance Comparison and Trust Evaluation","date":"2025-02-06","arxiv_id":"2502.06843","n_code_links":0,"syntology":null},{"paper":null,"slug":"yolov4-a-breakthrough-in-real-time-object","title":"YOLOv4: A Breakthrough in Real-Time Object Detection","date":"2025-02-06","arxiv_id":"2502.04161","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-beam-s-eye-view-to-fluence-maps-3d-network","title":"A Beam's Eye View to Fluence Maps 3D Network for Ultra Fast VMAT Radiotherapy Planning","date":"2025-02-05","arxiv_id":"2502.03360","n_code_links":0,"syntology":null},{"paper":"/paper/adaptive-voxel-weighted-loss-using-l1-norms","slug":"adaptive-voxel-weighted-loss-using-l1-norms","title":"Adaptive Voxel-Weighted Loss Using L1 Norms in Deep Neural Networks for Detection and Segmentation of Prostate Cancer Lesions in PET/CT Images","date":"2025-02-04","arxiv_id":"2502.02756","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-ensemble-approach-for-enhancing-brain","title":"Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings","date":"2025-02-04","arxiv_id":"2502.02179","n_code_links":0,"syntology":null},{"paper":"/paper/dual-flow-transferable-multi-target-instance","slug":"dual-flow-transferable-multi-target-instance","title":"Dual-Flow: Transferable Multi-Target, Instance-Agnostic Attacks via In-the-wild Cascading Flow Optimization","date":"2025-02-04","arxiv_id":"2502.02096","n_code_links":0,"syntology":{"ran":0,"of":3,"n_ran_checked":0,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"0 ran · 3 unverified","official":null}},{"paper":null,"slug":"exploring-the-latent-space-of-diffusion","title":"Exploring the latent space of diffusion models directly through singular value decomposition","date":"2025-02-04","arxiv_id":"2502.02225","n_code_links":0,"syntology":null},{"paper":"/paper/improving-power-plant-co2-emission-estimation","slug":"improving-power-plant-co2-emission-estimation","title":"Improving Power Plant CO2 Emission Estimation with Deep Learning and Satellite/Simulated Data","date":"2025-02-04","arxiv_id":"2502.02083","n_code_links":1,"syntology":null},{"paper":null,"slug":"spffnet-strip-perception-and-feature-fusion","title":"SPFFNet: Strip Perception and Feature Fusion Spatial Pyramid Pooling for Fabric Defect Detection","date":"2025-02-03","arxiv_id":"2502.01445","n_code_links":0,"syntology":null},{"paper":null,"slug":"boosting-adversarial-robustness-and","title":"Boosting Adversarial Robustness and Generalization with Structural Prior","date":"2025-02-02","arxiv_id":"2502.00834","n_code_links":0,"syntology":null},{"paper":"/paper/a-study-on-the-performance-of-u-net","slug":"a-study-on-the-performance-of-u-net","title":"A Study on the Performance of U-Net Modifications in Retroperitoneal Tumor Segmentation","date":"2025-02-01","arxiv_id":"2502.00314","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-learning-model-for-ecg-reconstruction","title":"Deep learning model for ECG reconstruction reveals the information content of ECG leads","date":"2025-02-01","arxiv_id":"2502.00559","n_code_links":0,"syntology":null},{"paper":null,"slug":"minimalistic-video-saliency-prediction-via","title":"Minimalistic Video Saliency Prediction via Efficient Decoder & Spatio Temporal Action Cues","date":"2025-02-01","arxiv_id":"2502.00397","n_code_links":0,"syntology":null},{"paper":"/paper/cerradata-4mm-a-multimodal-benchmark-dataset","slug":"cerradata-4mm-a-multimodal-benchmark-dataset","title":"CerraData-4MM: A multimodal benchmark dataset on Cerrado for land use and land cover classification","date":"2025-01-31","arxiv_id":"2502.00083","n_code_links":1,"syntology":null},{"paper":"/paper/full-scale-representation-guided-network-for","slug":"full-scale-representation-guided-network-for","title":"Full-scale Representation Guided Network for Retinal Vessel Segmentation","date":"2025-01-31","arxiv_id":"2501.18921","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-inductive-bias-of-infinite-depth","title":"On the inductive bias of infinite-depth ResNets and the bottleneck rank","date":"2025-01-31","arxiv_id":"2501.19149","n_code_links":0,"syntology":null},{"paper":"/paper/rmdm-radio-map-diffusion-model-with-physics","slug":"rmdm-radio-map-diffusion-model-with-physics","title":"RMDM: Radio Map Diffusion Model with Physics Informed","date":"2025-01-31","arxiv_id":"2501.19160","n_code_links":1,"syntology":null},{"paper":null,"slug":"cracks-in-concrete","title":"Cracks in concrete","date":"2025-01-30","arxiv_id":"2501.18376","n_code_links":0,"syntology":null},{"paper":"/paper/full-head-segmentation-of-mri-with-abnormal","slug":"full-head-segmentation-of-mri-with-abnormal","title":"Full-Head Segmentation of MRI with Abnormal Brain Anatomy: Model and Data Release","date":"2025-01-30","arxiv_id":"2501.18716","n_code_links":1,"syntology":null},{"paper":null,"slug":"segmentation-of-cracks-in-3d-images-of-fiber","title":"Segmentation of cracks in 3d images of fiber reinforced concrete using deep learning","date":"2025-01-30","arxiv_id":"2501.18405","n_code_links":0,"syntology":null},{"paper":null,"slug":"aggregation-schemes-for-single-vector-wsi","title":"Aggregation Schemes for Single-Vector WSI Representation Learning in Digital Pathology","date":"2025-01-29","arxiv_id":"2501.17822","n_code_links":0,"syntology":null},{"paper":"/paper/self-supervised-frameworks-for-speaker","slug":"self-supervised-frameworks-for-speaker","title":"Self-Supervised Frameworks for Speaker Verification via Bootstrapped Positive Sampling","date":"2025-01-29","arxiv_id":"2501.17772","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-m-factor-a-novel-metric-for-evaluating","title":"The M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments","date":"2025-01-29","arxiv_id":"2501.17361","n_code_links":0,"syntology":null},{"paper":"/paper/extending-information-bottleneck-attribution","slug":"extending-information-bottleneck-attribution","title":"Extending Information Bottleneck Attribution to Video Sequences","date":"2025-01-28","arxiv_id":"2501.16889","n_code_links":1,"syntology":null},{"paper":null,"slug":"post-training-quantization-for-3d-medical","title":"Post-Training Quantization for 3D Medical Image Segmentation: A Practical Study on Real Inference Engines","date":"2025-01-28","arxiv_id":"2501.17343","n_code_links":0,"syntology":null},{"paper":null,"slug":"separate-motion-from-appearance-customizing","title":"Separate Motion from Appearance: Customizing Motion via Customizing Text-to-Video Diffusion Models","date":"2025-01-28","arxiv_id":"2501.16714","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-object-detection-of-marine-debris","title":"Efficient Object Detection of Marine Debris using Pruned YOLO Model","date":"2025-01-27","arxiv_id":"2501.16571","n_code_links":0,"syntology":null},{"paper":null,"slug":"lsu-net-lightweight-automatic-organs","title":"LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images","date":"2025-01-27","arxiv_id":"2502.00042","n_code_links":0,"syntology":null},{"paper":"/paper/the-effect-of-optimal-self-distillation-in","slug":"the-effect-of-optimal-self-distillation-in","title":"The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model","date":"2025-01-27","arxiv_id":"2501.16226","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["taka255/self-distillation-analysis"],"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":"the-relationship-between-network-similarity","title":"The Relationship Between Network Similarity and Transferability of Adversarial Attacks","date":"2025-01-27","arxiv_id":"2501.18629","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-generative-models-to-produce-realistic-1","title":"Using Generative Models to Produce Realistic Populations of UK Windstorms","date":"2025-01-27","arxiv_id":"2501.16110","n_code_links":0,"syntology":null},{"paper":"/paper/ddunet-dual-dynamic-u-net-for-highly","slug":"ddunet-dual-dynamic-u-net-for-highly","title":"DDUNet: Dual Dynamic U-Net for Highly-Efficient Cloud Segmentation","date":"2025-01-26","arxiv_id":"2501.15385","n_code_links":1,"syntology":null},{"paper":null,"slug":"stroke-lesion-segmentation-using-multi-stage","title":"Stroke Lesion Segmentation using Multi-Stage Cross-Scale Attention","date":"2025-01-26","arxiv_id":"2501.15423","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-brownconrady-prediction-of-camera","title":"Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data","date":"2025-01-24","arxiv_id":"2501.14510","n_code_links":0,"syntology":null},{"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":"detection-and-classification-of-acute","title":"Detection and Classification of Acute Lymphoblastic Leukemia Utilizing Deep Transfer Learning","date":"2025-01-24","arxiv_id":"2501.14228","n_code_links":0,"syntology":null},{"paper":"/paper/improved-vessel-segmentation-with-symmetric","slug":"improved-vessel-segmentation-with-symmetric","title":"Improved Vessel Segmentation with Symmetric Rotation-Equivariant U-Net","date":"2025-01-24","arxiv_id":"2501.14592","n_code_links":1,"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":null,"slug":"training-free-style-and-content-transfer-by","title":"Training-Free Style and Content Transfer by Leveraging U-Net Skip Connections in Stable Diffusion 2.*","date":"2025-01-24","arxiv_id":"2501.14524","n_code_links":0,"syntology":null},{"paper":null,"slug":"uditqc-u-net-style-diffusion-transformer-for","title":"UDiTQC: U-Net-Style Diffusion Transformer for Quantum Circuit Synthesis","date":"2025-01-24","arxiv_id":"2501.16380","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":"/paper/enhancing-kelp-forest-detection-in-remote","slug":"enhancing-kelp-forest-detection-in-remote","title":"Enhancing kelp forest detection in remote sensing images using crowdsourced labels with Mixed Vision Transformers and ConvNeXt segmentation models","date":"2025-01-23","arxiv_id":"2501.14001","n_code_links":1,"syntology":null},{"paper":null,"slug":"enhancing-medical-image-analysis-through","title":"Enhancing Medical Image Analysis through Geometric and Photometric transformations","date":"2025-01-23","arxiv_id":"2501.13643","n_code_links":0,"syntology":null},{"paper":"/paper/llm-guided-instance-level-image-manipulation","slug":"llm-guided-instance-level-image-manipulation","title":"LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps","date":"2025-01-23","arxiv_id":"2501.14046","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/regularizing-cross-entropy-loss-via-minimum","slug":"regularizing-cross-entropy-loss-via-minimum","title":"Regularizing cross entropy loss via minimum entropy and K-L divergence","date":"2025-01-23","arxiv_id":"2501.13709","n_code_links":1,"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":"deep-learning-based-image-recovery-and-pose","title":"Deep Learning-Based Image Recovery and Pose Estimation for Resident Space Objects","date":"2025-01-22","arxiv_id":"2501.13009","n_code_links":0,"syntology":null},{"paper":"/paper/gamed-snake-gradient-aware-adaptive-momentum","slug":"gamed-snake-gradient-aware-adaptive-momentum","title":"GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation","date":"2025-01-22","arxiv_id":"2501.12844","n_code_links":1,"syntology":null},{"paper":null,"slug":"qufex-quantum-feature-extraction-module-for","title":"QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks","date":"2025-01-22","arxiv_id":"2501.13165","n_code_links":0,"syntology":null},{"paper":"/paper/an-end-to-end-approach-for-korean-wakeword","slug":"an-end-to-end-approach-for-korean-wakeword","title":"An End-to-End Approach for Korean Wakeword Systems with Speaker Authentication","date":"2025-01-21","arxiv_id":"2501.12194","n_code_links":2,"syntology":null},{"paper":null,"slug":"ccesar-coastline-classification-extraction","title":"CCESAR: Coastline Classification-Extraction From SAR Images Using CNN-U-Net Combination","date":"2025-01-21","arxiv_id":"2501.12384","n_code_links":0,"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":"comparative-analysis-of-hand-crafted-and","title":"Comparative Analysis of Hand-Crafted and Machine-Driven Histopathological Features for Prostate Cancer Classification and Segmentation","date":"2025-01-19","arxiv_id":"2501.12415","n_code_links":0,"syntology":null},{"paper":null,"slug":"deepeyenet-adaptive-genetic-bayesian","title":"DeepEyeNet: Adaptive Genetic Bayesian Algorithm Based Hybrid ConvNeXtTiny Framework For Multi-Feature Glaucoma Eye Diagnosis","date":"2025-01-19","arxiv_id":"2501.11168","n_code_links":0,"syntology":null},{"paper":"/paper/hierarchical-log-bayesian-neural-network-for","slug":"hierarchical-log-bayesian-neural-network-for","title":"Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation","date":"2025-01-18","arxiv_id":"2501.10615","n_code_links":1,"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/deep-learning-for-early-alzheimer-disease","slug":"deep-learning-for-early-alzheimer-disease","title":"Deep Learning for Early Alzheimer Disease Detection with MRI Scans","date":"2025-01-17","arxiv_id":"2501.09999","n_code_links":1,"syntology":null},{"paper":null,"slug":"high-resolution-tree-height-mapping-of-the","title":"High Resolution Tree Height Mapping of the Amazon Forest using Planet NICFI Images and LiDAR-Informed U-Net Model","date":"2025-01-17","arxiv_id":"2501.10600","n_code_links":0,"syntology":null},{"paper":"/paper/multi-modal-attention-networks-for-enhanced","slug":"multi-modal-attention-networks-for-enhanced","title":"Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse Thermography","date":"2025-01-17","arxiv_id":"2501.09994","n_code_links":1,"syntology":null},{"paper":null,"slug":"provably-safeguarding-a-classifier-from-ood","title":"Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach","date":"2025-01-17","arxiv_id":"2501.10202","n_code_links":0,"syntology":null},{"paper":null,"slug":"cancer-net-pca-seg-benchmarking-deep-learning","title":"Cancer-Net PCa-Seg: Benchmarking Deep Learning Models for Prostate Cancer Segmentation Using Synthetic Correlated Diffusion Imaging","date":"2025-01-15","arxiv_id":"2501.09185","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-distance-map-regression-network-with","title":"Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation","date":"2025-01-15","arxiv_id":"2501.09116","n_code_links":0,"syntology":null},{"paper":null,"slug":"relation-u-net","title":"Relation U-Net","date":"2025-01-15","arxiv_id":"2501.09101","n_code_links":0,"syntology":null},{"paper":null,"slug":"simgen-a-diffusion-based-framework-for","title":"SimGen: A Diffusion-Based Framework for Simultaneous Surgical Image and Segmentation Mask Generation","date":"2025-01-15","arxiv_id":"2501.09008","n_code_links":0,"syntology":null},{"paper":null,"slug":"timeflow-longitudinal-brain-image","title":"TimeFlow: Longitudinal Brain Image Registration and Aging Progression Analysis","date":"2025-01-15","arxiv_id":"2501.08667","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-feature-level-ensemble-model-for-covid-19","title":"A Feature-Level Ensemble Model for COVID-19 Identification in CXR Images using Choquet Integral and Differential Evolution Optimization","date":"2025-01-14","arxiv_id":"2501.08241","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/rwkv-unet-improving-unet-with-long-range","slug":"rwkv-unet-improving-unet-with-long-range","title":"RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation","date":"2025-01-14","arxiv_id":"2501.08458","n_code_links":1,"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":"blobgen-vid-compositional-text-to-video","title":"BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations","date":"2025-01-13","arxiv_id":"2501.07647","n_code_links":0,"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":"/paper/unetvl-enhancing-3d-medical-image","slug":"unetvl-enhancing-3d-medical-image","title":"UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM","date":"2025-01-13","arxiv_id":"2501.07017","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-label-scene-classification-in-remote","title":"Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution","date":"2025-01-12","arxiv_id":"2501.06720","n_code_links":0,"syntology":null},{"paper":null,"slug":"boundary-enhanced-time-series-data-imputation","title":"Boundary-enhanced time series data imputation with long-term dependency diffusion models","date":"2025-01-11","arxiv_id":"2501.06585","n_code_links":0,"syntology":null},{"paper":"/paper/cpdr-towards-highly-efficient-salient-object","slug":"cpdr-towards-highly-efficient-salient-object","title":"CPDR: Towards Highly-Efficient Salient Object Detection via Crossed Post-decoder Refinement","date":"2025-01-11","arxiv_id":"2501.06441","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":"/paper/parking-space-detection-in-the-city-of","slug":"parking-space-detection-in-the-city-of","title":"Parking Space Detection in the City of Granada","date":"2025-01-11","arxiv_id":"2501.06651","n_code_links":1,"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":"/paper/ucloudnet-a-residual-u-net-with-deep","slug":"ucloudnet-a-residual-u-net-with-deep","title":"UCloudNet: A Residual U-Net with Deep Supervision for Cloud Image Segmentation","date":"2025-01-11","arxiv_id":"2501.06440","n_code_links":1,"syntology":null},{"paper":"/paper/an-attention-guided-deep-learning-approach","slug":"an-attention-guided-deep-learning-approach","title":"An Attention-Guided Deep Learning Approach for Classifying 39 Skin Lesion Types","date":"2025-01-10","arxiv_id":"2501.05991","n_code_links":1,"syntology":null},{"paper":"/paper/3dis-flux-simple-and-efficient-multi-instance","slug":"3dis-flux-simple-and-efficient-multi-instance","title":"3DIS-FLUX: simple and efficient multi-instance generation with DiT rendering","date":"2025-01-09","arxiv_id":"2501.05131","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-systematic-literature-review-on-deep","title":"A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision","date":"2025-01-09","arxiv_id":"2501.05147","n_code_links":0,"syntology":null},{"paper":null,"slug":"explainable-ai-enhanced-deep-learning-for","title":"Explainable AI-Enhanced Deep Learning for Pumpkin Leaf Disease Detection: A Comparative Analysis of CNN Architectures","date":"2025-01-09","arxiv_id":"2501.05449","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-the-u-net-configuration-for","title":"Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRI","date":"2025-01-09","arxiv_id":"2501.05120","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":"efficient-and-accurate-tuberculosis-diagnosis","title":"Efficient and Accurate Tuberculosis Diagnosis: Attention Residual U-Net and Vision Transformer Based Detection Framework","date":"2025-01-07","arxiv_id":"2501.03538","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhanced-tuberculosis-bacilli-detection-using","title":"Enhanced Tuberculosis Bacilli Detection using Attention-Residual U-Net and Ensemble Classification","date":"2025-01-07","arxiv_id":"2501.03539","n_code_links":0,"syntology":null},{"paper":"/paper/image-segmentation-inducing-graph-based","slug":"image-segmentation-inducing-graph-based","title":"Image Segmentation: Inducing graph-based learning","date":"2025-01-07","arxiv_id":"2501.03765","n_code_links":1,"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":"framework-for-lung-ct-image-segmentation","title":"Framework for lung CT image segmentation based on UNet++","date":"2025-01-05","arxiv_id":"2501.02428","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":"ai-powered-cow-detection-in-complex-farm","title":"AI-Powered Cow Detection in Complex Farm Environments","date":"2025-01-03","arxiv_id":"2501.02080","n_code_links":0,"syntology":null}],"record_sha256":"c76bf3e15bfc7191ff538faa7d41c99e15981ada3518b0b5923409f46d0ee74e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}