{"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/convolution/papers/45","list_of":"/method/convolution","method":"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":45,"pages_in_order":196,"rows_per_page":100,"rows":[4401,4500],"of":19586,"counts":{"archive_papers_tagged":19586,"with_a_code_link":8064,"where_syntology_ran_a_sample":1837,"not_listed_spam_title":0,"listed":19586,"listed_where_code_ran":1837,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1557,"every_run_a_failure_of_syntologys_instrument":280,"listed_with_a_run_with_no_instrument_failure":1557,"listed_every_run_a_failure_of_syntologys_instrument":280,"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/convolution","prev":"/method/convolution/papers/44","next":"/method/convolution/papers/46","papers":[{"paper":null,"slug":"sparse-and-privacy-enhanced-representation","title":"Sparse and Privacy-enhanced Representation for Human Pose Estimation","date":"2023-09-18","arxiv_id":"2309.09515","n_code_links":0,"syntology":null},{"paper":"/paper/vsharp-variable-splitting-half-quadratic-admm","slug":"vsharp-variable-splitting-half-quadratic-admm","title":"vSHARP: variable Splitting Half-quadratic Admm algorithm for Reconstruction of inverse-Problems","date":"2023-09-18","arxiv_id":"2309.09954","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["nki-ai/direct"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/deep-neighbor-layer-aggregation-for","slug":"deep-neighbor-layer-aggregation-for","title":"Deep Neighbor Layer Aggregation for Lightweight Self-Supervised Monocular Depth Estimation","date":"2023-09-17","arxiv_id":"2309.09272","n_code_links":1,"syntology":null},{"paper":null,"slug":"bidirectional-graph-gan-representing-brain","title":"BG-GAN: Generative AI Enable Representing Brain Structure-Function Connections for Alzheimer's Disease","date":"2023-09-16","arxiv_id":"2309.08916","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparative-study-of-deep-learning-models-for","title":"Comparative study of Deep Learning Models for Binary Classification on Combined Pulmonary Chest X-ray Dataset","date":"2023-09-16","arxiv_id":"2309.10829","n_code_links":0,"syntology":null},{"paper":"/paper/dynamon-motion-aware-fast-and-robust-camera","slug":"dynamon-motion-aware-fast-and-robust-camera","title":"DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields","date":"2023-09-16","arxiv_id":"2309.08927","n_code_links":1,"syntology":null},{"paper":"/paper/pixel-adapter-a-graph-based-post-processing","slug":"pixel-adapter-a-graph-based-post-processing","title":"Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution","date":"2023-09-16","arxiv_id":"2309.08919","n_code_links":1,"syntology":null},{"paper":"/paper/3d-sa-unet-3d-spatial-attention-unet-with-3d","slug":"3d-sa-unet-3d-spatial-attention-unet-with-3d","title":"3D SA-UNet: 3D Spatial Attention UNet with 3D ASPP for White Matter Hyperintensities Segmentation","date":"2023-09-15","arxiv_id":"2309.08402","n_code_links":1,"syntology":null},{"paper":null,"slug":"cross-modal-synthesis-of-structural-mri-and","title":"Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs","date":"2023-09-15","arxiv_id":"2309.08160","n_code_links":0,"syntology":null},{"paper":null,"slug":"head-related-transfer-function-interpolation-1","title":"Head-Related Transfer Function Interpolation with a Spherical CNN","date":"2023-09-15","arxiv_id":"2309.08290","n_code_links":0,"syntology":null},{"paper":null,"slug":"hear-your-action-human-action-recognition-by","title":"hear-your-action: human action recognition by ultrasound active sensing","date":"2023-09-15","arxiv_id":"2309.08087","n_code_links":0,"syntology":null},{"paper":"/paper/hyperspectral-image-denoising-via-self","slug":"hyperspectral-image-denoising-via-self","title":"Hyperspectral Image Denoising via Self-Modulating Convolutional Neural Networks","date":"2023-09-15","arxiv_id":"2309.08197","n_code_links":1,"syntology":null},{"paper":null,"slug":"improved-breast-cancer-diagnosis-through","title":"Improved Breast Cancer Diagnosis through Transfer Learning on Hematoxylin and Eosin Stained Histology Images","date":"2023-09-15","arxiv_id":"2309.08745","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-short-utterance-anti-spoofing-with","title":"Improving Short Utterance Anti-Spoofing with AASIST2","date":"2023-09-15","arxiv_id":"2309.08279","n_code_links":0,"syntology":null},{"paper":"/paper/m-3-net-multilevel-mixed-and-multistage","slug":"m-3-net-multilevel-mixed-and-multistage","title":"M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection","date":"2023-09-15","arxiv_id":"2309.08365","n_code_links":1,"syntology":null},{"paper":"/paper/robust-burned-area-delineation-through","slug":"robust-burned-area-delineation-through","title":"Robust Burned Area Delineation through Multitask Learning","date":"2023-09-15","arxiv_id":"2309.08368","n_code_links":2,"syntology":null},{"paper":"/paper/salient-object-detection-in-optical-remote","slug":"salient-object-detection-in-optical-remote","title":"Salient Object Detection in Optical Remote Sensing Images Driven by Transformer","date":"2023-09-15","arxiv_id":"2309.08206","n_code_links":1,"syntology":null},{"paper":null,"slug":"toward-responsible-face-datasets-modeling-the","title":"Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups","date":"2023-09-15","arxiv_id":"2309.08442","n_code_links":0,"syntology":null},{"paper":null,"slug":"bea-revisiting-anchor-based-object-detection","title":"BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture","date":"2023-09-14","arxiv_id":"2309.08036","n_code_links":0,"syntology":null},{"paper":null,"slug":"complex-valued-neural-networks-for-data","title":"Complex-Valued Neural Networks for Data-Driven Signal Processing and Signal Understanding","date":"2023-09-14","arxiv_id":"2309.07948","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-based-dynamic-graph-convolutional","title":"Attention-based Dynamic Graph Convolutional Recurrent Neural Network for Traffic Flow Prediction in Highway Transportation","date":"2023-09-13","arxiv_id":"2309.07196","n_code_links":0,"syntology":null},{"paper":"/paper/cfdbench-a-comprehensive-benchmark-for","slug":"cfdbench-a-comprehensive-benchmark-for","title":"CFDBench: A Large-Scale Benchmark for Machine Learning Methods in Fluid Dynamics","date":"2023-09-13","arxiv_id":"2310.05963","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["luo-yining/cfdbench"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"efficient-quantum-recurrent-reinforcement","title":"Efficient quantum recurrent reinforcement learning via quantum reservoir computing","date":"2023-09-13","arxiv_id":"2309.07339","n_code_links":0,"syntology":null},{"paper":null,"slug":"mfl-yolo-an-object-detection-model-for","title":"MFL-YOLO: An Object Detection Model for Damaged Traffic Signs","date":"2023-09-13","arxiv_id":"2309.06750","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-step-prediction-of-chlorophyll","title":"Multi-step prediction of chlorophyll concentration based on Adaptive Graph-Temporal Convolutional Network with Series Decomposition","date":"2023-09-13","arxiv_id":"2309.07187","n_code_links":0,"syntology":null},{"paper":"/paper/2309-06212","slug":"2309-06212","title":"Long-term drought prediction using deep neural networks based on geospatial weather data","date":"2023-09-12","arxiv_id":"2309.06212","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-monotone-numerical-integration-method-for","title":"A monotone numerical integration method for mean-variance portfolio optimization under jump-diffusion models","date":"2023-09-12","arxiv_id":"2309.05977","n_code_links":0,"syntology":null},{"paper":null,"slug":"dslot-nn-digit-serial-left-to-right-neural","title":"DSLOT-NN: Digit-Serial Left-to-Right Neural Network Accelerator","date":"2023-09-12","arxiv_id":"2309.06019","n_code_links":0,"syntology":null},{"paper":null,"slug":"padding-free-convolution-based-on","title":"Padding-free Convolution based on Preservation of Differential Characteristics of Kernels","date":"2023-09-12","arxiv_id":"2309.06370","n_code_links":0,"syntology":null},{"paper":"/paper/advancing-parsimonious-deep-learning-weather","slug":"advancing-parsimonious-deep-learning-weather","title":"Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh","date":"2023-09-11","arxiv_id":"2311.06253","n_code_links":1,"syntology":null},{"paper":null,"slug":"anisotropic-diffusion-stencils-from-simple","title":"Anisotropic Diffusion Stencils: From Simple Derivations over Stability Estimates to ResNet Implementations","date":"2023-09-11","arxiv_id":"2309.05575","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-geometric-deep-learning-for","title":"Exploring Geometric Deep Learning For Precipitation Nowcasting","date":"2023-09-11","arxiv_id":"2309.05828","n_code_links":0,"syntology":null},{"paper":"/paper/fully-connected-spatial-temporal-graph-for","slug":"fully-connected-spatial-temporal-graph-for","title":"Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data","date":"2023-09-11","arxiv_id":"2309.05305","n_code_links":1,"syntology":null},{"paper":"/paper/learning-the-geodesic-embedding-with-graph","slug":"learning-the-geodesic-embedding-with-graph","title":"Learning the Geodesic Embedding with Graph Neural Networks","date":"2023-09-11","arxiv_id":"2309.05613","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["intelligentgeometry/gegnn"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"multiod-rehearsal-free-multihead-incremental","title":"MultIOD: Rehearsal-free Multihead Incremental Object Detector","date":"2023-09-11","arxiv_id":"2309.05334","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimizing-audio-augmentations-for","title":"Optimizing Audio Augmentations for Contrastive Learning of Health-Related Acoustic Signals","date":"2023-09-11","arxiv_id":"2309.05843","n_code_links":0,"syntology":null},{"paper":null,"slug":"our-deep-cnn-face-matchers-have-developed","title":"What's color got to do with it? Face recognition in grayscale","date":"2023-09-11","arxiv_id":"2309.05180","n_code_links":0,"syntology":null},{"paper":"/paper/semantic-latent-decomposition-with","slug":"semantic-latent-decomposition-with","title":"Semantic Latent Decomposition with Normalizing Flows for Face Editing","date":"2023-09-11","arxiv_id":"2309.05314","n_code_links":1,"syntology":null},{"paper":"/paper/lmbis-net-a-lightweight-multipath","slug":"lmbis-net-a-lightweight-multipath","title":"LMBiS-Net: A Lightweight Multipath Bidirectional Skip Connection based CNN for Retinal Blood Vessel Segmentation","date":"2023-09-10","arxiv_id":"2309.04968","n_code_links":1,"syntology":null},{"paper":"/paper/convformer-plug-and-play-cnn-style","slug":"convformer-plug-and-play-cnn-style","title":"ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation","date":"2023-09-09","arxiv_id":"2309.05674","n_code_links":1,"syntology":null},{"paper":"/paper/sshnn-semi-supervised-hybrid-nas-network-for","slug":"sshnn-semi-supervised-hybrid-nas-network-for","title":"SSHNN: Semi-Supervised Hybrid NAS Network for Echocardiographic Image Segmentation","date":"2023-09-09","arxiv_id":"2309.04672","n_code_links":1,"syntology":null},{"paper":null,"slug":"adversarial-attacks-on-hybrid-classical","title":"Adversarial attacks on hybrid classical-quantum Deep Learning models for Histopathological Cancer Detection","date":"2023-09-08","arxiv_id":"2309.06377","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-efficacy-of-multi-scale-data-samplers","title":"On the Efficacy of Multi-scale Data Samplers for Vision Applications","date":"2023-09-08","arxiv_id":"2309.04502","n_code_links":0,"syntology":null},{"paper":null,"slug":"weakly-supervised-point-clouds-transformer","title":"Weakly Supervised Point Clouds Transformer for 3D Object Detection","date":"2023-09-08","arxiv_id":"2309.04105","n_code_links":0,"syntology":null},{"paper":null,"slug":"adapting-self-supervised-representations-to","title":"Adapting Self-Supervised Representations to Multi-Domain Setups","date":"2023-09-07","arxiv_id":"2309.03999","n_code_links":0,"syntology":null},{"paper":"/paper/adversarially-robust-deep-learning-with","slug":"adversarially-robust-deep-learning-with","title":"Adversarially Robust Learning with Optimal Transport Regularized Divergences","date":"2023-09-07","arxiv_id":"2309.03791","n_code_links":1,"syntology":null},{"paper":"/paper/dataset-generation-and-bonobo-classification","slug":"dataset-generation-and-bonobo-classification","title":"Dataset Generation and Bonobo Classification from Weakly Labelled Videos","date":"2023-09-07","arxiv_id":"2309.03671","n_code_links":1,"syntology":null},{"paper":"/paper/dynamic-frame-interpolation-in-wavelet-domain","slug":"dynamic-frame-interpolation-in-wavelet-domain","title":"Dynamic Frame Interpolation in Wavelet Domain","date":"2023-09-07","arxiv_id":"2309.03508","n_code_links":1,"syntology":null},{"paper":null,"slug":"instance-segmentation-of-dislocations-in-tem","title":"Instance Segmentation of Dislocations in TEM Images","date":"2023-09-07","arxiv_id":"2309.03499","n_code_links":0,"syntology":null},{"paper":null,"slug":"ms-unet-v2-adaptive-denoising-method-and","title":"MS-UNet-v2: Adaptive Denoising Method and Training Strategy for Medical Image Segmentation with Small Training Data","date":"2023-09-07","arxiv_id":"2309.03686","n_code_links":0,"syntology":null},{"paper":null,"slug":"random-expert-sampling-for-deep-learning","title":"Random Expert Sampling for Deep Learning Segmentation of Acute Ischemic Stroke on Non-contrast CT","date":"2023-09-07","arxiv_id":"2309.03930","n_code_links":0,"syntology":null},{"paper":"/paper/stroke-based-neural-painting-and-stylization","slug":"stroke-based-neural-painting-and-stylization","title":"Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region","date":"2023-09-07","arxiv_id":"2309.03504","n_code_links":2,"syntology":null},{"paper":"/paper/an-efficient-temporary-deepfake-location","slug":"an-efficient-temporary-deepfake-location","title":"An Efficient Temporary Deepfake Location Approach Based Embeddings for Partially Spoofed Audio Detection","date":"2023-09-06","arxiv_id":"2309.03036","n_code_links":1,"syntology":null},{"paper":"/paper/diffusion-model-is-secretly-a-training-free","slug":"diffusion-model-is-secretly-a-training-free","title":"Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter","date":"2023-09-06","arxiv_id":"2309.02773","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["VCG-team/DiffSegmenter"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"dmkd-improving-feature-based-knowledge","title":"DMKD: Improving Feature-based Knowledge Distillation for Object Detection Via Dual Masking Augmentation","date":"2023-09-06","arxiv_id":"2309.02719","n_code_links":0,"syntology":null},{"paper":null,"slug":"dynamic-hyperbolic-attention-network-for-fine","title":"Dynamic Hyperbolic Attention Network for Fine Hand-object Reconstruction","date":"2023-09-06","arxiv_id":"2309.02965","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-training-for-visual-tracking-with","title":"Efficient Training for Visual Tracking with Deformable Transformer","date":"2023-09-06","arxiv_id":"2309.02676","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-level-rain-image-generative","title":"Hierarchical-level rain image generative model based on GAN","date":"2023-09-06","arxiv_id":"2309.02964","n_code_links":0,"syntology":null},{"paper":null,"slug":"kidney-abnormality-segmentation-in-thorax","title":"Kidney abnormality segmentation in thorax-abdomen CT scans","date":"2023-09-06","arxiv_id":"2309.03383","n_code_links":0,"syntology":null},{"paper":"/paper/knowledge-distillation-layer-that-lets-the","slug":"knowledge-distillation-layer-that-lets-the","title":"Knowledge Distillation Layer that Lets the Student Decide","date":"2023-09-06","arxiv_id":"2309.02843","n_code_links":1,"syntology":null},{"paper":null,"slug":"r2d2-deep-neural-network-series-for-near-real","title":"CLEANing Cygnus A deep and fast with R2D2","date":"2023-09-06","arxiv_id":"2309.03291","n_code_links":0,"syntology":null},{"paper":null,"slug":"rgb-camera-based-blood-pressure-measurement","title":"RGB Camera-Based Blood Pressure Measurement Using U-Net Basic Generative Model","date":"2023-09-06","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluation-kidney-layer-segmentation-on-whole","title":"Evaluation Kidney Layer Segmentation on Whole Slide Imaging using Convolutional Neural Networks and Transformers","date":"2023-09-05","arxiv_id":"2309.02563","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploiting-spatial-temporal-data-for-sleep","title":"Exploiting Spatial-temporal Data for Sleep Stage Classification via Hypergraph Learning","date":"2023-09-05","arxiv_id":"2309.02124","n_code_links":0,"syntology":null},{"paper":"/paper/inceptnet-precise-and-early-disease-detection","slug":"inceptnet-precise-and-early-disease-detection","title":"INCEPTNET: Precise And Early Disease Detection Application For Medical Images Analyses","date":"2023-09-05","arxiv_id":"2309.02147","n_code_links":1,"syntology":null},{"paper":null,"slug":"ohq-on-chip-hardware-aware-quantization","title":"On-Chip Hardware-Aware Quantization for Mixed Precision Neural Networks","date":"2023-09-05","arxiv_id":"2309.01945","n_code_links":0,"syntology":null},{"paper":null,"slug":"performance-analysis-of-various-efficientnet","title":"Performance Analysis of Various EfficientNet Based U-Net++ Architecture for Automatic Building Extraction from High Resolution Satellite Images","date":"2023-09-05","arxiv_id":"2310.06847","n_code_links":0,"syntology":null},{"paper":null,"slug":"sasdim-self-adaptive-noise-scaling-diffusion","title":"sasdim: self-adaptive noise scaling diffusion model for spatial time series imputation","date":"2023-09-05","arxiv_id":"2309.01988","n_code_links":0,"syntology":null},{"paper":"/paper/self-similarity-based-and-novelty-based-loss","slug":"self-similarity-based-and-novelty-based-loss","title":"Self-Similarity-Based and Novelty-based loss for music structure analysis","date":"2023-09-05","arxiv_id":"2309.02243","n_code_links":2,"syntology":null},{"paper":"/paper/the-adversarial-implications-of-variable-time","slug":"the-adversarial-implications-of-variable-time","title":"The Adversarial Implications of Variable-Time Inference","date":"2023-09-05","arxiv_id":"2309.02159","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-fpga-smart-camera-implementation-of","title":"An FPGA smart camera implementation of segmentation models for drone wildfire imagery","date":"2023-09-04","arxiv_id":"2309.01318","n_code_links":0,"syntology":null},{"paper":null,"slug":"defect-detection-in-synthetic-fibre-ropes","title":"Defect Detection in Synthetic Fibre Ropes using Detectron2 Framework","date":"2023-09-04","arxiv_id":"2309.01469","n_code_links":0,"syntology":null},{"paper":null,"slug":"fau-net-an-attention-u-net-extension-with","title":"FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation","date":"2023-09-04","arxiv_id":"2309.01322","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-constraint-matching-transformer-for","title":"Semantic-Constraint Matching Transformer for Weakly Supervised Object Localization","date":"2023-09-04","arxiv_id":"2309.01331","n_code_links":0,"syntology":null},{"paper":null,"slug":"single-channel-speech-enhancement-with-deep","title":"Single-Channel Speech Enhancement with Deep Complex U-Networks and Probabilistic Latent Space Models","date":"2023-09-04","arxiv_id":"2309.01535","n_code_links":0,"syntology":null},{"paper":null,"slug":"ab2cd-ai-for-building-climate-damage","title":"AB2CD: AI for Building Climate Damage Classification and Detection","date":"2023-09-03","arxiv_id":"2309.01066","n_code_links":0,"syntology":null},{"paper":"/paper/an-asynchronous-linear-filter-architecture","slug":"an-asynchronous-linear-filter-architecture","title":"An Asynchronous Linear Filter Architecture for Hybrid Event-Frame Cameras","date":"2023-09-03","arxiv_id":"2309.01159","n_code_links":1,"syntology":null},{"paper":null,"slug":"channel-attention-separable-convolution","title":"Channel Attention Separable Convolution Network for Skin Lesion Segmentation","date":"2023-09-03","arxiv_id":"2309.01072","n_code_links":0,"syntology":null},{"paper":"/paper/deep-unfolding-convolutional-dictionary-model","slug":"deep-unfolding-convolutional-dictionary-model","title":"Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and Reconstruction","date":"2023-09-03","arxiv_id":"2309.01171","n_code_links":1,"syntology":{"ran":11,"of":14,"n_ran_checked":10,"n_instrument":1,"unverified":3,"pointer_only":0,"phrase":"11 ran (of which 9 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["lpcccc-cv/mc-cdic"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":9,"n_ran_no_instrument_failure":10,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"user-lung-cancer-classification-using","title":"User lung cancer classification using efficientnet from ct scan images","date":"2023-09-03","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"comparative-analysis-of-deep-learning-2","title":"Comparative Analysis of Deep Learning Architectures for Breast Cancer Diagnosis Using the BreaKHis Dataset","date":"2023-09-02","arxiv_id":"2309.01007","n_code_links":0,"syntology":null},{"paper":"/paper/constrained-cyclegan-for-effective-generation","slug":"constrained-cyclegan-for-effective-generation","title":"Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial Resolution","date":"2023-09-02","arxiv_id":"2309.00995","n_code_links":1,"syntology":null},{"paper":null,"slug":"gramian-angular-fields-for-leveraging","title":"Gramian Angular Fields for leveraging pretrained computer vision models with anomalous diffusion trajectories","date":"2023-09-02","arxiv_id":"2310.01416","n_code_links":0,"syntology":null},{"paper":"/paper/a-locality-based-neural-solver-for-optical","slug":"a-locality-based-neural-solver-for-optical","title":"A Locality-based Neural Solver for Optical Motion Capture","date":"2023-09-01","arxiv_id":"2309.00428","n_code_links":1,"syntology":null},{"paper":"/paper/dacl10k-benchmark-for-semantic-bridge-damage","slug":"dacl10k-benchmark-for-semantic-bridge-damage","title":"dacl10k: Benchmark for Semantic Bridge Damage Segmentation","date":"2023-09-01","arxiv_id":"2309.00460","n_code_links":1,"syntology":null},{"paper":"/paper/mechanism-of-feature-learning-in","slug":"mechanism-of-feature-learning-in","title":"Mechanism of feature learning in convolutional neural networks","date":"2023-09-01","arxiv_id":"2309.00570","n_code_links":1,"syntology":{"ran":10,"of":17,"n_ran_checked":10,"n_instrument":0,"unverified":7,"pointer_only":17,"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":["aradha/convrfm"],"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":null,"slug":"muranet-multi-task-floor-plan-recognition","title":"MuraNet: Multi-task Floor Plan Recognition with Relation Attention","date":"2023-09-01","arxiv_id":"2309.00348","n_code_links":0,"syntology":null},{"paper":null,"slug":"rignet-efficient-repetitive-image-guided","title":"RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion","date":"2023-09-01","arxiv_id":"2309.00655","n_code_links":0,"syntology":null},{"paper":null,"slug":"sortednet-a-place-for-every-network-and-every","title":"SortedNet: A Scalable and Generalized Framework for Training Modular Deep Neural Networks","date":"2023-09-01","arxiv_id":"2309.00255","n_code_links":0,"syntology":null},{"paper":"/paper/beyond-self-attention-deformable-large-kernel","slug":"beyond-self-attention-deformable-large-kernel","title":"Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation","date":"2023-08-31","arxiv_id":"2309.00121","n_code_links":1,"syntology":null},{"paper":"/paper/coarse-to-fine-amodal-segmentation-with-shape","slug":"coarse-to-fine-amodal-segmentation-with-shape","title":"Coarse-to-Fine Amodal Segmentation with Shape Prior","date":"2023-08-31","arxiv_id":"2308.16825","n_code_links":1,"syntology":null},{"paper":null,"slug":"deformation-robust-text-spotting-with","title":"Deformation Robust Text Spotting with Geometric Prior","date":"2023-08-31","arxiv_id":"2308.16404","n_code_links":0,"syntology":null},{"paper":null,"slug":"document-layout-analysis-on-badlad-dataset-a","title":"Document Layout Analysis on BaDLAD Dataset: A Comprehensive MViTv2 Based Approach","date":"2023-08-31","arxiv_id":"2308.16571","n_code_links":0,"syntology":null},{"paper":"/paper/irregular-traffic-time-series-forecasting","slug":"irregular-traffic-time-series-forecasting","title":"Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network","date":"2023-08-31","arxiv_id":"2308.16818","n_code_links":1,"syntology":{"ran":3,"of":5,"n_ran_checked":3,"n_instrument":0,"unverified":2,"pointer_only":5,"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) · 2 unverified","official":{"repos":["usail-hkust/aseer"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"object-detection-for-caries-or-pit-and","title":"Object Detection for Caries or Pit and Fissure Sealing Requirement in Children's First Permanent Molars","date":"2023-08-31","arxiv_id":"2308.16551","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-gan-inversion","title":"Robust GAN inversion","date":"2023-08-31","arxiv_id":"2308.16510","n_code_links":0,"syntology":null},{"paper":null,"slug":"segmentacao-e-contagem-de-troncos-de-madeira","title":"Segmentação e contagem de troncos de madeira utilizando deep learning e processamento de imagens","date":"2023-08-31","arxiv_id":"2309.00123","n_code_links":0,"syntology":null},{"paper":"/paper/self-supervised-semantic-segmentation-1","slug":"self-supervised-semantic-segmentation-1","title":"Self-supervised Semantic Segmentation: Consistency over Transformation","date":"2023-08-31","arxiv_id":"2309.00143","n_code_links":1,"syntology":null},{"paper":"/paper/styleinv-a-temporal-style-modulated-inversion","slug":"styleinv-a-temporal-style-modulated-inversion","title":"StyleInV: A Temporal Style Modulated Inversion Network for Unconditional Video Generation","date":"2023-08-31","arxiv_id":"2308.16909","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"0 ran · 2 unverified","official":{"repos":["johannwyh/styleinv"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"paper":"/paper/towards-optimal-patch-size-in-vision","slug":"towards-optimal-patch-size-in-vision","title":"Towards Optimal Patch Size in Vision Transformers for Tumor Segmentation","date":"2023-08-31","arxiv_id":"2308.16598","n_code_links":1,"syntology":null}],"record_sha256":"d2022f108428783b10c448b69c195c82f54fad831d83a25658e28e63bad4ab0f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}