{"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":"/task/image-augmentation/papers/3","list_of":"/task/image-augmentation","task":"Image Augmentation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":3,"pages_in_order":4,"rows_per_page":100,"rows":[201,300],"of":308,"counts":{"archive_papers_tagged":308,"with_a_code_link":127,"where_syntology_ran_a_sample":30,"not_listed_spam_title":0,"listed":308,"listed_where_code_ran":30,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":27,"every_run_a_failure_of_syntologys_instrument":3,"listed_with_a_run_with_no_instrument_failure":27,"listed_every_run_a_failure_of_syntologys_instrument":3,"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":"/task/image-augmentation","prev":"/task/image-augmentation/papers/2","next":"/task/image-augmentation/papers/4","papers":[{"url":null,"slug":"augdiff-diffusion-based-feature-augmentation","title":"AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Image","date":"2023-03-11","arxiv_id":"2303.06371","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-composable-distributions-of-latent","title":"Towards Composable Distributions of Latent Space Augmentations","date":"2023-03-06","arxiv_id":"2303.03462","repositories_listed":0,"syntology":null},{"url":null,"slug":"lmseg-language-guided-multi-dataset","title":"LMSeg: Language-guided Multi-dataset Segmentation","date":"2023-02-27","arxiv_id":"2302.13495","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-guided-image-augmentation-with-pre","title":"Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification","date":"2023-02-04","arxiv_id":"2302.02070","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-convolutional-neural-network-of-low","title":"A convolutional neural network of low complexity for tumor anomaly detection","date":"2023-01-24","arxiv_id":"2301.09861","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-image-representation-learning-1","title":"Self-Supervised Image Representation Learning: Transcending Masking with Paired Image Overlay","date":"2023-01-23","arxiv_id":"2301.09299","repositories_listed":0,"syntology":null},{"url":null,"slug":"development-of-a-prototype-application-for","title":"Development of a Prototype Application for Rice Disease Detection Using Convolutional Neural Networks","date":"2023-01-13","arxiv_id":"2301.05528","repositories_listed":0,"syntology":null},{"url":null,"slug":"design-of-arabic-sign-language-recognition","title":"Design of Arabic Sign Language Recognition Model","date":"2023-01-06","arxiv_id":"2301.02693","repositories_listed":0,"syntology":null},{"url":null,"slug":"misalign-contrast-then-distill-rethinking","title":"Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pre-training","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"diagnosis-of-covid-19-based-on-chest","title":"Diagnosis of COVID-19 based on Chest Radiography","date":"2022-12-26","arxiv_id":"2212.13032","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditioned-generative-transformers-for","title":"Unified Framework for Histopathology Image Augmentation and Classification via Generative Models","date":"2022-12-20","arxiv_id":"2212.09977","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-augmentation-with-conformal-mappings","title":"Image augmentation with conformal mappings for a convolutional neural network","date":"2022-12-10","arxiv_id":"2212.05258","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-communication-enabling-robust-edge","title":"Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications","date":"2022-11-24","arxiv_id":"2211.13787","repositories_listed":0,"syntology":null},{"url":null,"slug":"design-of-an-efficient-distracted-driver","title":"Design of an Efficient Distracted Driver Detection System: Deep Learning Approaches","date":"2022-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cmt-interpretable-model-for-rapid-recognition","title":"Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images","date":"2022-10-29","arxiv_id":"2210.16584","repositories_listed":0,"syntology":null},{"url":null,"slug":"rawgment-noise-accounted-raw-augmentation","title":"Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments","date":"2022-10-28","arxiv_id":"2210.16046","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-object-detection-based-on","title":"Semi-supervised object detection based on single-stage detector for thighbone fracture localization","date":"2022-10-20","arxiv_id":"2210.10998","repositories_listed":0,"syntology":null},{"url":null,"slug":"plant-species-classification-using-transfer","title":"Plant Species Classification Using Transfer Learning by Pretrained Classifier VGG-19","date":"2022-09-07","arxiv_id":"2209.03076","repositories_listed":0,"syntology":null},{"url":null,"slug":"compound-figure-separation-of-biomedical-1","title":"Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning","date":"2022-08-30","arxiv_id":"2208.14357","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-augmentation-improves-few-shot","title":"Image augmentation improves few-shot classification performance in plant disease recognition","date":"2022-08-25","arxiv_id":"2208.12613","repositories_listed":0,"syntology":null},{"url":null,"slug":"semaug-semantically-meaningful-image","title":"SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding","date":"2022-08-15","arxiv_id":"2208.07407","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-augmentation-for-satellite-images","title":"Image Augmentation for Satellite Images","date":"2022-07-29","arxiv_id":"2207.14580","repositories_listed":0,"syntology":null},{"url":null,"slug":"water-surface-patch-classification-using","title":"River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index","date":"2022-07-13","arxiv_id":"2207.06388","repositories_listed":0,"syntology":null},{"url":null,"slug":"game-state-learning-via-game-scene","title":"Game State Learning via Game Scene Augmentation","date":"2022-07-04","arxiv_id":"2207.01289","repositories_listed":0,"syntology":null},{"url":null,"slug":"augment-to-detect-anomalies-with-continuous","title":"Augment to Detect Anomalies with Continuous Labelling","date":"2022-07-03","arxiv_id":"2207.01112","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-temporally-dynamic-data","title":"Exploring Temporally Dynamic Data Augmentation for Video Recognition","date":"2022-06-30","arxiv_id":"2206.15015","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-classification-of-brain-tumor-images","title":"Multi-Classification of Brain Tumor Images Using Transfer Learning Based Deep Neural Network","date":"2022-06-17","arxiv_id":"2206.08543","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-automated-data-augmentation","title":"A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks","date":"2022-06-14","arxiv_id":"2206.06544","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-augmentation-based-momentum-memory","title":"Image Augmentation Based Momentum Memory Intrinsic Reward for Sparse Reward Visual Scenes","date":"2022-05-19","arxiv_id":"2205.09448","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-neural-networks-learning-from-scratch","title":"Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization","date":"2022-05-18","arxiv_id":"2205.08836","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-of-image-augmentation","title":"A Comprehensive Survey of Image Augmentation Techniques for Deep Learning","date":"2022-05-03","arxiv_id":"2205.01491","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmentation-techniques-analysis-with-removal","title":"Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/improving-model-performance-and-removing-the","slug":"improving-model-performance-and-removing-the","title":"Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"resnet18-model-with-sequential-layer-for","title":"Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"epicardial-adipose-tissue-segmentation-from","title":"Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network","date":"2022-04-27","arxiv_id":"2204.12904","repositories_listed":0,"syntology":null},{"url":null,"slug":"pneumonia-detection-in-chest-x-rays-using","title":"Pneumonia Detection in Chest X-Rays using Neural Networks","date":"2022-04-07","arxiv_id":"2204.03618","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-synthesize-volumetric-meshes-from","title":"Learning to Synthesize Volumetric Meshes from Vision-based Tactile Imprints","date":"2022-03-29","arxiv_id":"2203.15155","repositories_listed":0,"syntology":null},{"url":null,"slug":"transparency-strategy-based-data-augmentation","title":"A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms","date":"2022-03-20","arxiv_id":"2203.10609","repositories_listed":0,"syntology":null},{"url":null,"slug":"fourier-based-augmentations-for-improved","title":"Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration","date":"2022-02-24","arxiv_id":"2202.12412","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-efficient-training-of-progressive","title":"Time Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network","date":"2022-02-24","arxiv_id":"2202.12337","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-residual-encoder-decoder-network-for","title":"A Residual Encoder-Decoder Network for Segmentation of Retinal Image-Based Exudates in Diabetic Retinopathy Screening","date":"2022-01-16","arxiv_id":"2201.05963","repositories_listed":0,"syntology":null},{"url":"/paper/a-data-driven-approach-to-improve-3d-head","slug":"a-data-driven-approach-to-improve-3d-head","title":"A Data-Driven Approach to Improve 3D Head-Pose Estimation","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-hierarchical-refinement-and-augmentation","title":"3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video","date":"2021-12-06","arxiv_id":"2112.03045","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-tale-of-color-variants-representation-and","title":"A Tale of Color Variants: Representation and Self-Supervised Learning in Fashion E-Commerce","date":"2021-12-06","arxiv_id":"2112.02910","repositories_listed":0,"syntology":null},{"url":null,"slug":"document-layout-analysis-with-aesthetic","title":"Document Layout Analysis with Aesthetic-Guided Image Augmentation","date":"2021-11-27","arxiv_id":"2111.13809","repositories_listed":0,"syntology":null},{"url":null,"slug":"explanatory-analysis-and-rectification-of-the","title":"Explanatory Analysis and Rectification of the Pitfalls in COVID-19 Datasets","date":"2021-11-10","arxiv_id":"2111.05679","repositories_listed":0,"syntology":null},{"url":null,"slug":"segmentation-of-multiple-myeloma-plasma-cells","title":"Segmentation of Multiple Myeloma Plasma Cells in Microscopy Images with Noisy Labels","date":"2021-11-08","arxiv_id":"2111.05125","repositories_listed":0,"syntology":null},{"url":null,"slug":"attention-w-net-improved-skip-connections-for","title":"Attention W-Net: Improved Skip Connections for better Representations","date":"2021-10-17","arxiv_id":"2110.08811","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-methodology-to-identify-cognition-gaps-in","title":"A Methodology to Identify Cognition Gaps in Visual Recognition Applications Based on Convolutional Neural Networks","date":"2021-10-05","arxiv_id":"2110.02080","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-technical-report-for-iccv-2021-vipriors-re","title":"A Technical Report for ICCV 2021 VIPriors Re-identification Challenge","date":"2021-09-30","arxiv_id":"2109.15164","repositories_listed":0,"syntology":null},{"url":null,"slug":"aug-ila-more-transferable-intermediate-level","title":"Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fitvid-high-capacity-pixel-level-video","title":"FitVid: High-Capacity Pixel-Level Video Prediction","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-robust-agents-for-visual-navigation","title":"Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge","date":"2021-09-22","arxiv_id":"2109.10493","repositories_listed":0,"syntology":null},{"url":null,"slug":"wind-turbine-blade-surface-damage-detection","title":"Wind Turbine Blade Surface Damage Detection based on Aerial Imagery and VGG16-RCNN Framework","date":"2021-08-19","arxiv_id":"2108.08636","repositories_listed":0,"syntology":null},{"url":null,"slug":"compound-figure-separation-of-biomedical","title":"Compound Figure Separation of Biomedical Images with Side Loss","date":"2021-07-19","arxiv_id":"2107.08650","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-fault-detection-in-industrial-welding","title":"Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation","date":"2021-06-18","arxiv_id":"2106.10160","repositories_listed":0,"syntology":null},{"url":null,"slug":"pathology-aware-generative-adversarial","title":"Pathology-Aware Generative Adversarial Networks for Medical Image Augmentation","date":"2021-06-03","arxiv_id":"2106.01915","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-based-augmentation-improves-quality-of","title":"Object-Based Augmentation Improves Quality of Remote Sensing Semantic Segmentation","date":"2021-05-12","arxiv_id":"2105.05516","repositories_listed":0,"syntology":null},{"url":null,"slug":"fish-disease-detection-using-image-based","title":"Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture","date":"2021-05-09","arxiv_id":"2105.03934","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-networks-for-semantic-gaze-analysis-in","title":"Neural Networks for Semantic Gaze Analysis in XR Settings","date":"2021-03-18","arxiv_id":"2103.10451","repositories_listed":0,"syntology":null},{"url":"/paper/hierarchical-attention-based-age-estimation","slug":"hierarchical-attention-based-age-estimation","title":"Hierarchical Attention-based Age Estimation and Bias Estimation","date":"2021-03-17","arxiv_id":"2103.09882","repositories_listed":0,"syntology":null},{"url":null,"slug":"worsening-perception-real-time-degradation-of","title":"Worsening Perception: Real-time Degradation of Autonomous Vehicle Perception Performance for Simulation of Adverse Weather Conditions","date":"2021-03-03","arxiv_id":"2103.02760","repositories_listed":0,"syntology":null},{"url":null,"slug":"reducing-labelled-data-requirement-for","title":"Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentations","date":"2021-02-25","arxiv_id":"2102.12764","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-impact-of-interpretability-methods-in","title":"On the Impact of Interpretability Methods in Active Image Augmentation Method","date":"2021-02-24","arxiv_id":"2102.12354","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-u-net-for-domain-free","title":"Generative Adversarial U-Net for Domain-free Medical Image Augmentation","date":"2021-01-12","arxiv_id":"2101.04793","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-object-focused-images-as-an-image","title":"USING OBJECT-FOCUSED IMAGES AS AN IMAGE AUGMENTATION TECHNIQUE TO IMPROVE THE ACCURACY OF IMAGE-CLASSIFICATION MODELS WHEN VERY LIMITED DATA SETS ARE AVAILABLE","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-methods-for-screening-pulmonary","title":"Deep Learning Methods for Screening Pulmonary Tuberculosis Using Chest X-rays","date":"2020-12-25","arxiv_id":"2012.13582","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-gan-based-image-augmentation-for","title":"Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images","date":"2020-12-23","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-performance-improvement-in-indian","title":"Towards Performance Improvement in Indian Sign Language Recognition","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fusiformnet-extracting-discriminative-facial","title":"FusiformNet: Extracting Discriminative Facial Features on Different Levels","date":"2020-11-01","arxiv_id":"2011.00577","repositories_listed":0,"syntology":null},{"url":null,"slug":"cimon-towards-high-quality-hash-codes","title":"CIMON: Towards High-quality Hash Codes","date":"2020-10-15","arxiv_id":"2010.07804","repositories_listed":0,"syntology":null},{"url":null,"slug":"face-mask-detection-using-transfer-learning","title":"Face Mask Detection using Transfer Learning of InceptionV3","date":"2020-09-17","arxiv_id":"2009.08369","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-action-recognition-system-for-smart","title":"A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning","date":"2020-09-07","arxiv_id":"2009.03285","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-technical-report-for-vipriors-image","title":"A Technical Report for VIPriors Image Classification Challenge","date":"2020-07-17","arxiv_id":"2007.08722","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-probabilistic-framework-for-discriminative","title":"A Probabilistic Model for Discriminative and Neuro-Symbolic Semi-Supervised Learning","date":"2020-06-10","arxiv_id":"2006.05896","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-augmentations-for-gan-training","title":"Image Augmentations for GAN Training","date":"2020-06-04","arxiv_id":"2006.02595","repositories_listed":0,"syntology":null},{"url":null,"slug":"polarimetric-image-augmentation","title":"Polarimetric image augmentation","date":"2020-05-22","arxiv_id":"2005.11044","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-image-generation-using-generative","title":"Medical Image Generation using Generative Adversarial Networks","date":"2020-05-19","arxiv_id":"2005.10687","repositories_listed":0,"syntology":null},{"url":null,"slug":"temperate-fish-detection-and-classification-a","title":"Temperate Fish Detection and Classification: a Deep Learning based Approach","date":"2020-05-14","arxiv_id":"2005.07518","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-image-augmentation-for-damage","title":"Synthetic Image Augmentation for Damage Region Segmentation using Conditional GAN with Structure Edge","date":"2020-05-07","arxiv_id":"2005.08628","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-partial-intrinsic-and-extrinsic","title":"Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging","date":"2020-03-04","arxiv_id":"2003.02294","repositories_listed":0,"syntology":null},{"url":null,"slug":"pose-aware-instance-segmentation-framework","title":"Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation","date":"2020-02-06","arxiv_id":"2002.02143","repositories_listed":0,"syntology":null},{"url":null,"slug":"inter-slice-image-augmentation-based-on-frame","title":"Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy","date":"2020-01-31","arxiv_id":"2001.11698","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-phantom-test-pattern-classification","title":"Automatic phantom test pattern classification through transfer learning with deep neural networks","date":"2020-01-22","arxiv_id":"2001.08189","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-the-gap-between-ai-and-healthcare","title":"Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems","date":"2020-01-12","arxiv_id":"2001.03923","repositories_listed":0,"syntology":null},{"url":null,"slug":"decision-support-system-for-detection-and","title":"Decision Support System for Detection and Classification of Skin Cancer using CNN","date":"2019-12-09","arxiv_id":"1912.03798","repositories_listed":0,"syntology":null},{"url":null,"slug":"fuzzy-semantic-segmentation-of-breast","title":"Fuzzy Semantic Segmentation of Breast Ultrasound Image with Breast Anatomy Constraints","date":"2019-09-14","arxiv_id":"1909.06645","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-cnn-toolbox-for-skin-cancer-classification","title":"A CNN toolbox for skin cancer classification","date":"2019-08-21","arxiv_id":"1908.08187","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-image-augmentation-for-improved","title":"Synthetic Image Augmentation for Improved Classification using Generative Adversarial Networks","date":"2019-07-31","arxiv_id":"1907.13576","repositories_listed":0,"syntology":null},{"url":null,"slug":"slot-based-image-augmentation-system-for","title":"Slot Based Image Augmentation System for Object Detection","date":"2019-07-19","arxiv_id":"1907.12900","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-colon-polyp-detection-using-region","title":"Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches","date":"2019-06-27","arxiv_id":"1906.11463","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthesizing-diverse-lung-nodules-wherever","title":"Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detection","date":"2019-06-12","arxiv_id":"1906.04962","repositories_listed":0,"syntology":null},{"url":null,"slug":"landslide-geohazard-assessment-with","title":"Landslide Geohazard Assessment With Convolutional Neural Networks Using Sentinel-2 Imagery Data","date":"2019-06-10","arxiv_id":"1906.06151","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-noise-to-image-and-image-to-image","title":"Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection","date":"2019-05-31","arxiv_id":"1905.13456","repositories_listed":0,"syntology":null},{"url":null,"slug":"super-resolution-convolutional-neural-network","title":"Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images","date":"2019-04-16","arxiv_id":"1904.07470","repositories_listed":0,"syntology":null},{"url":null,"slug":"biometric-fish-classification-of-temperate","title":"Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation","date":"2019-04-04","arxiv_id":"1904.02768","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-more-with-less-gan-based-medical","title":"Learning More with Less: GAN-based Medical Image Augmentation","date":"2019-03-29","arxiv_id":"1904.00838","repositories_listed":0,"syntology":null},{"url":null,"slug":"yelp-food-identification-via-image-feature","title":"Yelp Food Identification via Image Feature Extraction and Classification","date":"2019-02-11","arxiv_id":"1902.05413","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-augmentation-via-data-subsampling","title":"Efficient Augmentation via Data Subsampling","date":"2018-10-11","arxiv_id":"1810.05222","repositories_listed":0,"syntology":null},{"url":null,"slug":"sensor-transfer-learning-optimal-sensor","title":"Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation","date":"2018-09-17","arxiv_id":"1809.06256","repositories_listed":0,"syntology":null}],"record_sha256":"5a012318f107e69863565768cbddb23c72e70f0db922ab204309eb9b60e0d832","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}