{"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/deep-learning/papers/85","list_of":"/task/deep-learning","task":"Deep Learning","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":85,"pages_in_order":95,"rows_per_page":100,"rows":[8401,8500],"of":9423,"counts":{"archive_papers_tagged":9423,"with_a_code_link":2693,"where_syntology_ran_a_sample":410,"not_listed_spam_title":0,"listed":9423,"listed_where_code_ran":410,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":356,"every_run_a_failure_of_syntologys_instrument":54,"listed_with_a_run_with_no_instrument_failure":356,"listed_every_run_a_failure_of_syntologys_instrument":54,"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/deep-learning","prev":"/task/deep-learning/papers/84","next":"/task/deep-learning/papers/86","papers":[{"url":null,"slug":"deep-learning-for-image-denoising-a-survey","title":"Deep Learning for Image Denoising: A Survey","date":"2018-10-11","arxiv_id":"1810.05052","repositories_listed":0,"syntology":null},{"url":null,"slug":"policy-design-for-active-sequential","title":"Policy Design for Active Sequential Hypothesis Testing using Deep Learning","date":"2018-10-11","arxiv_id":"1810.04859","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-institutional-deep-learning-modeling","title":"Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation","date":"2018-10-10","arxiv_id":"1810.04304","repositories_listed":0,"syntology":null},{"url":null,"slug":"secure-deep-learning-engineering-a-software","title":"Secure Deep Learning Engineering: A Software Quality Assurance Perspective","date":"2018-10-10","arxiv_id":"1810.04538","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimized-gated-deep-learning-architectures","title":"Optimized Gated Deep Learning Architectures for Sensor Fusion","date":"2018-10-08","arxiv_id":"1810.04160","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-extrapolation-tool-for-ab","title":"Deep learning: Extrapolation tool for ab initio nuclear theory","date":"2018-10-06","arxiv_id":"1810.04009","repositories_listed":0,"syntology":null},{"url":null,"slug":"wide-and-deep-learning-for-peer-to-peer","title":"Wide and Deep Learning for Peer-to-Peer Lending","date":"2018-10-05","arxiv_id":"1810.03466","repositories_listed":0,"syntology":null},{"url":null,"slug":"polar-feature-based-deep-architectures-for","title":"Polar Feature Based Deep Architectures for Automatic Modulation Classification Considering Channel Fading","date":"2018-10-04","arxiv_id":"1810.02027","repositories_listed":0,"syntology":null},{"url":null,"slug":"181009230","title":"AST-Based Deep Learning for Detecting Malicious PowerShell","date":"2018-10-03","arxiv_id":"1810.09230","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-architecture-for-de","title":"A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation","date":"2018-10-03","arxiv_id":"1810.01570","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-pipeline-for-product","title":"A deep learning pipeline for product recognition on store shelves","date":"2018-10-03","arxiv_id":"1810.01733","repositories_listed":0,"syntology":null},{"url":null,"slug":"theory-of-generative-deep-learning-probe","title":"Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control","date":"2018-10-03","arxiv_id":"1810.01622","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-warship-combining-components-of-brain","title":"Towards WARSHIP: Combining Components of Brain-Inspired Computing of RSH for Image Super Resolution","date":"2018-10-03","arxiv_id":"1810.01620","repositories_listed":0,"syntology":null},{"url":null,"slug":"cloud-chaser-real-time-deep-learning-computer","title":"Cloud Chaser: Real Time Deep Learning Computer Vision on Low Computing Power Devices","date":"2018-10-02","arxiv_id":"1810.01069","repositories_listed":0,"syntology":null},{"url":null,"slug":"promid-human-promoter-prediction-by-deep","title":"PromID: human promoter prediction by deep learning","date":"2018-10-02","arxiv_id":"1810.01414","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-identification-of-drugs-and-adverse","title":"Automatic Identification of Drugs and Adverse Drug Reaction Related Tweets","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-social-media-health-text","title":"Deep Learning for Social Media Health Text Classification","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-sparse-graph-for-efficient-deep","title":"Dynamic Sparse Graph for Efficient Deep Learning","date":"2018-10-01","arxiv_id":"1810.00859","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-alzheimers-disease-diagnosis-and","title":"End-To-End Alzheimer's Disease Diagnosis and Biomarker Identification","date":"2018-10-01","arxiv_id":"1810.00523","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-and-learning-suicidal-ideation","title":"Exploring and Learning Suicidal Ideation Connotations on Social Media with Deep Learning","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-optimism-and-pessimism-in-twitter","title":"Exploring Optimism and Pessimism in Twitter Using Deep Learning","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-end-to-end-atrial","title":"Deep Learning for End-to-End Atrial Fibrillation Recurrence Estimation","date":"2018-09-30","arxiv_id":"1810.00475","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-attacks-and-defences-a-survey","title":"Adversarial Attacks and Defences: A Survey","date":"2018-09-28","arxiv_id":"1810.00069","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-systems-as-complex-networks","title":"Deep learning systems as complex networks","date":"2018-09-28","arxiv_id":"1809.10941","repositories_listed":0,"syntology":null},{"url":null,"slug":"interest-point-detectors-stability-evaluation","title":"Interest point detectors stability evaluation on ApolloScape dataset","date":"2018-09-28","arxiv_id":"1809.11039","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-proposed-hierarchy-of-deep-learning-tasks","title":"A Proposed Hierarchy of Deep Learning Tasks","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-solution-to-china-competitive-poker-using","title":"A Solution to China Competitive Poker Using Deep Learning","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"image-reconstruction-using-deep-learning","title":"Image Reconstruction Using Deep Learning","date":"2018-09-27","arxiv_id":"1809.10410","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-generative-adversarial-imitation","title":"Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"merci-a-new-metric-to-evaluate-the","title":"MERCI: A NEW METRIC TO EVALUATE THE CORRELATION BETWEEN PREDICTIVE UNCERTAINTY AND TRUE ERROR","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reduced-gate-convolutional-lstm-design-using","title":"Reduced-Gate Convolutional LSTM Design Using Predictive Coding for Next-Frame Video Prediction","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-increased-trustworthiness-of-deep","title":"Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI","date":"2018-09-27","arxiv_id":"1809.10430","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-more-theoretically-grounded-particle","title":"Towards More Theoretically-Grounded Particle Optimization Sampling for Deep Learning","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-confidence-a-computationally-efficient","title":"Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks","date":"2018-09-24","arxiv_id":"1809.09060","repositories_listed":0,"syntology":null},{"url":null,"slug":"identification-and-visualization-of-the","title":"Identification and Visualization of the Underlying Independent Causes of the Diagnostic of Diabetic Retinopathy made by a Deep Learning Classifier","date":"2018-09-23","arxiv_id":"1809.08567","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-denoising-and-super-resolution-using","title":"Image Denoising and Super-Resolution using Residual Learning of Deep Convolutional Network","date":"2018-09-21","arxiv_id":"1809.08229","repositories_listed":0,"syntology":null},{"url":null,"slug":"duplo-a-dual-view-point-deep-learning","title":"DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn","date":"2018-09-20","arxiv_id":"1809.07589","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-rib-centerline-extraction","title":"Deep Learning Based Rib Centerline Extraction and Labeling","date":"2018-09-19","arxiv_id":"1809.07082","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-on-deep-learning-based-sauvegrain","title":"A Study on Deep Learning Based Sauvegrain Method for Measurement of Puberty Bone Age","date":"2018-09-18","arxiv_id":"1809.06965","repositories_listed":0,"syntology":null},{"url":null,"slug":"power-market-price-forecasting-via-deep","title":"Power Market Price Forecasting via Deep Learning","date":"2018-09-18","arxiv_id":"1809.08092","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-framework-for-unsupervised","title":"A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration","date":"2018-09-17","arxiv_id":"1809.06130","repositories_listed":0,"syntology":null},{"url":null,"slug":"autonomous-exploration-reconstruction-and","title":"Greedy Algorithms for Sparse Sensor Placement via Deep Learning","date":"2018-09-17","arxiv_id":"1809.06025","repositories_listed":0,"syntology":null},{"url":null,"slug":"intermediate-deep-feature-compression-the","title":"Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing","date":"2018-09-17","arxiv_id":"1809.06196","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-driven-deep-learning-for-physical-layer","title":"Model-Driven Deep Learning for Physical Layer Communications","date":"2018-09-17","arxiv_id":"1809.06059","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-investigation-of-a-deep-learning-based","title":"An investigation of a deep learning based malware detection system","date":"2018-09-16","arxiv_id":"1809.05888","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparison-of-deep-learning-and-the-classical","title":"Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection","date":"2018-09-16","arxiv_id":"1809.05889","repositories_listed":0,"syntology":null},{"url":null,"slug":"development-of-deep-learning-algorithms-to","title":"Development of deep learning algorithms to categorize free-text notes pertaining to diabetes: convolution neural networks achieve higher accuracy than support vector machines","date":"2018-09-16","arxiv_id":"1809.05814","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-stage-algorithm-for-acoustic-physical","title":"A Multi-Stage Algorithm for Acoustic Physical Model Parameters Estimation","date":"2018-09-14","arxiv_id":"1809.05483","repositories_listed":0,"syntology":null},{"url":null,"slug":"macquarie-university-at-bioasq-6b-deep-1","title":"Macquarie University at BioASQ 6b: Deep learning and deep reinforcement learning for query-based multi-document summarisation","date":"2018-09-14","arxiv_id":"1809.05283","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-examples-opportunities-and","title":"Adversarial Examples: Opportunities and Challenges","date":"2018-09-13","arxiv_id":"1809.04790","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-neural-network-approach-for-eeg","title":"Convolutional Neural Network Approach for EEG-based Emotion Recognition using Brain Connectivity and its Spatial Information","date":"2018-09-12","arxiv_id":"1809.04208","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-information-security","title":"Deep Learning in Information Security","date":"2018-09-12","arxiv_id":"1809.04332","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-computing-platforms-for-deep","title":"Comparing Computing Platforms for Deep Learning on a Humanoid Robot","date":"2018-09-11","arxiv_id":"1809.03668","repositories_listed":0,"syntology":null},{"url":"/paper/efficient-road-lane-marking-detection-with","slug":"efficient-road-lane-marking-detection-with","title":"Efficient Road Lane Marking Detection with Deep Learning","date":"2018-09-11","arxiv_id":"1809.03994","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-can-linguistics-and-deep-learning","title":"What can linguistics and deep learning contribute to each other?","date":"2018-09-11","arxiv_id":"1809.04179","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-case-for-deep-learning-in-semantics","title":"A case for deep learning in semantics","date":"2018-09-10","arxiv_id":"1809.03068","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-similarity-network-for-evaluating","title":"Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning Based Registration","date":"2018-09-10","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"approximation-and-estimation-for-high","title":"Approximation and Estimation for High-Dimensional Deep Learning Networks","date":"2018-09-10","arxiv_id":"1809.03090","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-towards-mobile-applications","title":"Deep Learning Towards Mobile Applications","date":"2018-09-10","arxiv_id":"1809.03559","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-preserving-deep-learning-via-weight","title":"Privacy-Preserving Deep Learning via Weight Transmission","date":"2018-09-10","arxiv_id":"1809.03272","repositories_listed":0,"syntology":null},{"url":null,"slug":"urban-i-from-urban-scenes-to-mapping-slums","title":"URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision","date":"2018-09-10","arxiv_id":"1809.03609","repositories_listed":0,"syntology":null},{"url":null,"slug":"phaselink-a-deep-learning-approach-to-seismic","title":"PhaseLink: A Deep Learning Approach to Seismic Phase Association","date":"2018-09-08","arxiv_id":"1809.02880","repositories_listed":0,"syntology":null},{"url":"/paper/unsupervised-person-re-identification-by-deep-1","slug":"unsupervised-person-re-identification-by-deep-1","title":"Unsupervised Person Re-identification by Deep Learning Tracklet Association","date":"2018-09-08","arxiv_id":"1809.02874","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-decoding-for-constrained","title":"Deep Learning-Based Decoding for Constrained Sequence Codes","date":"2018-09-06","arxiv_id":"1809.01859","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-generic-object-detection-a","title":"Deep Learning for Generic Object Detection: A Survey","date":"2018-09-06","arxiv_id":"1809.02165","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-in-vitro-prediction-of","title":"Deep learning for in vitro prediction of pharmaceutical formulations","date":"2018-09-06","arxiv_id":"1809.02069","repositories_listed":0,"syntology":null},{"url":null,"slug":"deeply-learning-derivatives","title":"Deeply Learning Derivatives","date":"2018-09-06","arxiv_id":"1809.02233","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometry-of-deep-learning-for-magnetic","title":"Geometry of Deep Learning for Magnetic Resonance Fingerprinting","date":"2018-09-05","arxiv_id":"1809.01749","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-spatiotemporal-prediction","title":"A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services","date":"2018-09-04","arxiv_id":"1809.00811","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-reassembly-combining-deep-learning-and","title":"Image Reassembly Combining Deep Learning and Shortest Path Problem","date":"2018-09-04","arxiv_id":"1809.00898","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-the-expressiveness-of-deep-learning","title":"Improving the Expressiveness of Deep Learning Frameworks with Recursion","date":"2018-09-04","arxiv_id":"1809.00832","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-spectral-fusion-by-combining-deep","title":"Spatial-Spectral Fusion by Combining Deep Learning and Variation Model","date":"2018-09-04","arxiv_id":"1809.00764","repositories_listed":0,"syntology":null},{"url":"/paper/unsupervised-video-object-segmentation-using","slug":"unsupervised-video-object-segmentation-using","title":"Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation","date":"2018-09-04","arxiv_id":"1809.01125","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-reassembly-combining-deep-learning-and-1","title":"Image Reassembly Combining Deep Learning and Shortest Path Problem","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"proximal-dehaze-net-a-prior-learning-based","title":"Proximal Dehaze-Net: A Prior Learning-Based Deep Network for Single Image Dehazing","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"transductive-semi-supervised-deep-learning","title":"Transductive Semi-Supervised Deep Learning using Min-Max Features","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simplified-approach-to-deep-learning-for","title":"A Simplified Approach to Deep Learning for Image Segmentation","date":"2018-08-31","arxiv_id":"1809.00085","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-neural-pathways-in-zebrafish","title":"Understanding Neural Pathways in Zebrafish through Deep Learning and High Resolution Electron Microscope Data","date":"2018-08-31","arxiv_id":"1809.00084","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-analysis-of-stochastic-momentum","title":"A Unified Analysis of Stochastic Momentum Methods for Deep Learning","date":"2018-08-30","arxiv_id":"1808.10396","repositories_listed":0,"syntology":null},{"url":null,"slug":"backdoor-embedding-in-convolutional-neural","title":"Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation","date":"2018-08-30","arxiv_id":"1808.10307","repositories_listed":0,"syntology":null},{"url":null,"slug":"securing-tag-based-recommender-systems-1","title":"Securing Tag-based recommender systems against profile injection attacks: A comparative study","date":"2018-08-30","arxiv_id":"1808.10550","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-computational-aspects","title":"Deep Learning: Computational Aspects","date":"2018-08-26","arxiv_id":"1808.08618","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-brief-survey-and-an-application-of-semantic","title":"A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving","date":"2018-08-25","arxiv_id":"1808.08413","repositories_listed":0,"syntology":null},{"url":null,"slug":"msce-an-edge-preserving-robust-loss-function","title":"MSCE: An edge preserving robust loss function for improving super-resolution algorithms","date":"2018-08-25","arxiv_id":"1809.00961","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-attacks-on-deep-learning-based","title":"Adversarial Attacks on Deep-Learning Based Radio Signal Classification","date":"2018-08-23","arxiv_id":"1808.07713","repositories_listed":0,"syntology":null},{"url":null,"slug":"brain-biomarker-interpretation-in-asd-using","title":"Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI","date":"2018-08-23","arxiv_id":"1808.08296","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-frame-rate-cardiac-ultrasound-imaging","title":"High frame-rate cardiac ultrasound imaging with deep learning","date":"2018-08-23","arxiv_id":"1808.07823","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-quality-ultrasonic-multi-line","title":"High quality ultrasonic multi-line transmission through deep learning","date":"2018-08-23","arxiv_id":"1808.07819","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-modern-object-detection","title":"A Survey of Modern Object Detection Literature using Deep Learning","date":"2018-08-22","arxiv_id":"1808.07256","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepcorr-strong-flow-correlation-attacks-on","title":"DeepCorr: Strong Flow Correlation Attacks on Tor Using Deep Learning","date":"2018-08-22","arxiv_id":"1808.07285","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-patient-generation-a-deep-learning","title":"Synthetic Patient Generation: A Deep Learning Approach Using Variational Autoencoders","date":"2018-08-20","arxiv_id":"1808.06444","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-breast-cancer-detection-using","title":"Improving Breast Cancer Detection using Symmetry Information with Deep Learning","date":"2018-08-17","arxiv_id":"1808.08273","repositories_listed":0,"syntology":null},{"url":null,"slug":"conceptual-domain-adaptation-using-deep","title":"Conceptual Domain Adaptation Using Deep Learning","date":"2018-08-16","arxiv_id":"1808.05355","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-energy-markets","title":"Deep Learning for Energy Markets","date":"2018-08-16","arxiv_id":"1808.05527","repositories_listed":0,"syntology":null},{"url":null,"slug":"tool-breakage-detection-using-deep-learning","title":"Tool Breakage Detection using Deep Learning","date":"2018-08-16","arxiv_id":"1808.05347","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepdownscale-a-deep-learning-strategy-for","title":"DeepDownscale: a Deep Learning Strategy for High-Resolution Weather Forecast","date":"2018-08-15","arxiv_id":"1808.05264","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-deep-learning-for-persian","title":"Exploiting Deep Learning for Persian Sentiment Analysis","date":"2018-08-15","arxiv_id":"1808.05077","repositories_listed":0,"syntology":null},{"url":"/paper/cosmoflow-using-deep-learning-to-learn-the","slug":"cosmoflow-using-deep-learning-to-learn-the","title":"CosmoFlow: Using Deep Learning to Learn the Universe at Scale","date":"2018-08-14","arxiv_id":"1808.04728","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-framework-for-digital-breast","title":"Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction","date":"2018-08-14","arxiv_id":"1808.04640","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-plaque-detection-in-ivoct-pullbacks","title":"Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks","date":"2018-08-13","arxiv_id":"1808.04187","repositories_listed":0,"syntology":null}],"record_sha256":"cd28a1232349923abdb4f5c0dd2c68b13df2e6f96fd08e00007823433b782a5a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}