{"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/82","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":82,"pages_in_order":95,"rows_per_page":100,"rows":[8101,8200],"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/81","next":"/task/deep-learning/papers/83","papers":[{"url":null,"slug":"accelerated-nuclear-magnetic-resonance","title":"Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning","date":"2019-04-09","arxiv_id":"1904.05168","repositories_listed":0,"syntology":null},{"url":null,"slug":"novel-uncertainty-framework-for-deep-learning","title":"Novel Uncertainty Framework for Deep Learning Ensembles","date":"2019-04-09","arxiv_id":"1904.04917","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-computed-tomography-whys","title":"Deep Learning Based Computed Tomography Whys and Wherefores","date":"2019-04-08","arxiv_id":"1904.03908","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-the-eeg-manifold-for","title":"Deep Learning the EEG Manifold for Phonological Categorization from Active Thoughts","date":"2019-04-08","arxiv_id":"1904.04358","repositories_listed":0,"syntology":null},{"url":"/paper/spi-gcn-a-simple-permutation-invariant-graph","slug":"spi-gcn-a-simple-permutation-invariant-graph","title":"SPI-GCN: A Simple Permutation-Invariant Graph Convolutional Network","date":"2019-04-08","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-deep-epipolar-flow-for","title":"Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes","date":"2019-04-08","arxiv_id":"1904.03848","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-bottleneck-and-its-applications","title":"Information Bottleneck and its Applications in Deep Learning","date":"2019-04-07","arxiv_id":"1904.03743","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-compendium-on-network-and-host-based","title":"A Compendium on Network and Host based Intrusion Detection Systems","date":"2019-04-06","arxiv_id":"1904.03491","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-universal-beamformer-for","title":"Deep Learning-based Universal Beamformer for Ultrasound Imaging","date":"2019-04-05","arxiv_id":"1904.02843","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessment-of-faster-r-cnn-in-man-machine","title":"Assessment of Faster R-CNN in Man-Machine collaborative search","date":"2019-04-04","arxiv_id":"1904.02805","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-sentiment-analysis-of-amazoncom","title":"Deep Learning Sentiment Analysis of Amazon.com Reviews and Ratings","date":"2019-04-04","arxiv_id":"1904.04096","repositories_listed":0,"syntology":null},{"url":null,"slug":"malware-detection-using-machine-learning-and","title":"Malware Detection using Machine Learning and Deep Learning","date":"2019-04-04","arxiv_id":"1904.02441","repositories_listed":0,"syntology":null},{"url":"/paper/3d-bevis-birds-eye-view-instance-segmentation","slug":"3d-bevis-birds-eye-view-instance-segmentation","title":"3D-BEVIS: Bird's-Eye-View Instance Segmentation","date":"2019-04-03","arxiv_id":"1904.02199","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentially-private-model-publishing-for","title":"Differentially Private Model Publishing for Deep Learning","date":"2019-04-03","arxiv_id":"1904.02200","repositories_listed":0,"syntology":null},{"url":null,"slug":"empirical-study-of-deep-learning-for-text","title":"Empirical Study of Deep Learning for Text Classification in Legal Document Review","date":"2019-04-03","arxiv_id":"1904.01723","repositories_listed":0,"syntology":null},{"url":null,"slug":"barista-efficient-and-scalable-serverless","title":"BARISTA: Efficient and Scalable Serverless Serving System for Deep Learning Prediction Services","date":"2019-04-02","arxiv_id":"1904.01576","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-face-recognition-pride-or","title":"Deep Learning for Face Recognition: Pride or Prejudiced?","date":"2019-04-02","arxiv_id":"1904.01219","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlling-for-biasing-signals-in-images-for","title":"Controlling for Biasing Signals in Images for Prognostic Models: Survival Predictions for Lung Cancer with Deep Learning","date":"2019-04-01","arxiv_id":"1904.00942","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-methods-for-parallel-magnetic","title":"Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction","date":"2019-04-01","arxiv_id":"1904.01112","repositories_listed":0,"syntology":null},{"url":null,"slug":"early-diagnosis-of-pneumonia-with-deep","title":"Early Diagnosis of Pneumonia with Deep Learning","date":"2019-04-01","arxiv_id":"1904.00937","repositories_listed":0,"syntology":null},{"url":null,"slug":"190409029","title":"Deep Learning for Power System Security Assessment","date":"2019-03-31","arxiv_id":"1904.09029","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-arrhythmia-detection-by-deep-learning-and","title":"On Arrhythmia Detection by Deep Learning and Multidimensional Representation","date":"2019-03-30","arxiv_id":"1904.00138","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-dive-into-understanding-tumor-foci","title":"A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network","date":"2019-03-29","arxiv_id":"1903.12331","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-many-objective-radiomics-and-3d","title":"Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer","date":"2019-03-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-relational-representations-with-auto","title":"Learning Relational Representations with Auto-encoding Logic Programs","date":"2019-03-29","arxiv_id":"1903.12577","repositories_listed":0,"syntology":null},{"url":null,"slug":"rapid-early-classification-of-explosive","title":"RAPID: Early Classification of Explosive Transients using Deep Learning","date":"2019-03-29","arxiv_id":"1904.00014","repositories_listed":0,"syntology":null},{"url":null,"slug":"yet-another-accelerated-sgd-resnet-50","title":"Yet Another Accelerated SGD: ResNet-50 Training on ImageNet in 74.7 seconds","date":"2019-03-29","arxiv_id":"1903.12650","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-defect-segmentation-on-leather-with","title":"Automatic Defect Segmentation on Leather with Deep Learning","date":"2019-03-28","arxiv_id":"1903.12139","repositories_listed":0,"syntology":null},{"url":null,"slug":"nearest-neighbor-neural-networks-for","title":"Nearest-Neighbor Neural Networks for Geostatistics","date":"2019-03-28","arxiv_id":"1903.12125","repositories_listed":0,"syntology":null},{"url":null,"slug":"supersymmetric-artificial-neural-network","title":"Supersymmetric Artificial Neural Network","date":"2019-03-28","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-framework-for-automatic-detection-of","title":"A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD)","date":"2019-03-27","arxiv_id":"1903.11323","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-deep-learning-in-eeg-biometrics","title":"Adversarial Deep Learning in EEG Biometrics","date":"2019-03-27","arxiv_id":"1903.11673","repositories_listed":0,"syntology":null},{"url":null,"slug":"rallying-adversarial-techniques-against-deep","title":"Rallying Adversarial Techniques against Deep Learning for Network Security","date":"2019-03-27","arxiv_id":"1903.11688","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-deep-learning-on-distributed","title":"Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques and Tools","date":"2019-03-27","arxiv_id":"1903.11314","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-localization-in-the-lung","title":"Deep Learning for Localization in the Lung","date":"2019-03-25","arxiv_id":"1903.10554","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-attribute-selectivity-estimation-using","title":"Multi-Attribute Selectivity Estimation Using Deep Learning","date":"2019-03-24","arxiv_id":"1903.09999","repositories_listed":0,"syntology":null},{"url":null,"slug":"scene-understanding-for-autonomous","title":"Scene Understanding for Autonomous Manipulation with Deep Learning","date":"2019-03-23","arxiv_id":"1903.09761","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-fictitious-play-for-stochastic","title":"Deep Fictitious Play for Stochastic Differential Games","date":"2019-03-22","arxiv_id":"1903.09376","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-data-augmentation-for-deep-learning","title":"Data Augmentation for Bayesian Deep Learning","date":"2019-03-22","arxiv_id":"1903.09668","repositories_listed":0,"syntology":null},{"url":null,"slug":"190409274","title":"Deep Learning on Mobile Devices - A Review","date":"2019-03-21","arxiv_id":"1904.09274","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-models-for-deep-learning-with-very","title":"Generative Models For Deep Learning with Very Scarce Data","date":"2019-03-21","arxiv_id":"1903.09030","repositories_listed":0,"syntology":null},{"url":null,"slug":"skelneton-2019-dataset-and-challenge-on-deep","title":"SkelNetOn 2019: Dataset and Challenge on Deep Learning for Geometric Shape Understanding","date":"2019-03-21","arxiv_id":"1903.09233","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-semi-supervised-deep-learning-algorithm-for","title":"A semi-supervised deep learning algorithm for abnormal EEG identification","date":"2019-03-19","arxiv_id":"1903.07822","repositories_listed":0,"syntology":null},{"url":null,"slug":"offline-and-online-deep-learning-for-image","title":"Offline and Online Deep Learning for Image Recognition","date":"2019-03-18","arxiv_id":"1903.07479","repositories_listed":0,"syntology":null},{"url":null,"slug":"offenseval-at-semeval-2018-task-6-identifying","title":"Absit invidia verbo: Comparing Deep Learning methods for offensive language","date":"2019-03-14","arxiv_id":"1903.05929","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepcount-crowd-counting-with-wifi-via-deep","title":"DeepCount: Crowd Counting with WiFi via Deep Learning","date":"2019-03-13","arxiv_id":"1903.05316","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-automated-medical-image","title":"Deep Learning for Automated Medical Image Analysis","date":"2019-03-12","arxiv_id":"1903.04711","repositories_listed":0,"syntology":null},{"url":null,"slug":"ax-dbn-an-approximate-computing-framework-for","title":"AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks","date":"2019-03-11","arxiv_id":"1903.04659","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-asset-pricing-1","title":"Deep Learning in Asset Pricing","date":"2019-03-11","arxiv_id":"1904.00745","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradient-descent-based-optimization","title":"Gradient Descent based Optimization Algorithms for Deep Learning Models Training","date":"2019-03-11","arxiv_id":"1903.03614","repositories_listed":0,"syntology":null},{"url":null,"slug":"inceptiongcn-receptive-field-aware-graph","title":"InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction","date":"2019-03-11","arxiv_id":"1903.04233","repositories_listed":0,"syntology":null},{"url":null,"slug":"approximating-optimisation-solutions-for","title":"Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network","date":"2019-03-08","arxiv_id":"1903.03348","repositories_listed":0,"syntology":null},{"url":null,"slug":"based-on-graph-vae-model-to-predict-students","title":"Based on Graph-VAE Model to Predict Student's Score","date":"2019-03-08","arxiv_id":"1903.03609","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-online-power-control-for","title":"Deep Learning Based Online Power Control for Large Energy Harvesting Networks","date":"2019-03-08","arxiv_id":"1903.03652","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-capsule-unified-framework-of-deep-neural","title":"A Capsule-unified Framework of Deep Neural Networks for Graphical Programming","date":"2019-03-07","arxiv_id":"1903.04982","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-at-scale-for-gravitational-wave","title":"Statistically-informed deep learning for gravitational wave parameter estimation","date":"2019-03-05","arxiv_id":"1903.01998","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-medical-image-registration-a","title":"Deep Learning in Medical Image Registration: A Survey","date":"2019-03-05","arxiv_id":"1903.02026","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-pulse-shape","title":"Deep learning based pulse shape discrimination for germanium detectors","date":"2019-03-04","arxiv_id":"1903.01462","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-cognitive-neuroscience","title":"Deep Learning for Cognitive Neuroscience","date":"2019-03-04","arxiv_id":"1903.01458","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-the-mechanism-of-deep-learning","title":"Understanding the Mechanism of Deep Learning Framework for Lesion Detection in Pathological Images with Breast Cancer","date":"2019-03-04","arxiv_id":"1903.01214","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-delay-momentum-a-regularization","title":"Time-Delay Momentum: A Regularization Perspective on the Convergence and Generalization of Stochastic Momentum for Deep Learning","date":"2019-03-02","arxiv_id":"1903.00760","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-design-exploration-by-integrating","title":"Deep Generative Design: Integration of Topology Optimization and Generative Models","date":"2019-03-01","arxiv_id":"1903.01548","repositories_listed":0,"syntology":null},{"url":null,"slug":"financial-series-prediction-using-attention","title":"Financial series prediction using Attention LSTM","date":"2019-02-28","arxiv_id":"1902.10877","repositories_listed":0,"syntology":null},{"url":null,"slug":"spda-superpixel-based-data-augmentation-for","title":"SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation","date":"2019-02-28","arxiv_id":"1903.00035","repositories_listed":0,"syntology":null},{"url":null,"slug":"speeding-up-deep-learning-with-transient","title":"Speeding up Deep Learning with Transient Servers","date":"2019-02-28","arxiv_id":"1903.00045","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-inference-to-measure-model","title":"Variational Inference to Measure Model Uncertainty in Deep Neural Networks","date":"2019-02-26","arxiv_id":"1902.10189","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-detailed-comparative-study-of-open-source","title":"A detailed comparative study of open source deep learning frameworks","date":"2019-02-25","arxiv_id":"1903.00102","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-low-dose-ct-denoising","title":"Deep Learning for Low-Dose CT Denoising","date":"2019-02-25","arxiv_id":"1902.10127","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-approach-on-information","title":"Deep Learning Approach on Information Diffusion in Heterogeneous Networks","date":"2019-02-23","arxiv_id":"1902.08810","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-in-cardiology","title":"Deep Learning in Cardiology","date":"2019-02-22","arxiv_id":"1902.11122","repositories_listed":0,"syntology":null},{"url":null,"slug":"cmr-motion-artifact-correction-using","title":"CMR motion artifact correction using generative adversarial nets","date":"2019-02-21","arxiv_id":"1902.11121","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-multidimensional-projections","title":"Deep Learning Multidimensional Projections","date":"2019-02-21","arxiv_id":"1902.07958","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-tube-amplifier-emulation","title":"Deep Learning for Tube Amplifier Emulation","date":"2019-02-20","arxiv_id":"1811.00334","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-automatic-segmentation-of-amygdala","title":"Accurate Automatic Segmentation of Amygdala Subnuclei and Modeling of Uncertainty via Bayesian Fully Convolutional Neural Network","date":"2019-02-19","arxiv_id":"1902.07289","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-memory-management-for-gpu-based","title":"Efficient Memory Management for GPU-based Deep Learning Systems","date":"2019-02-19","arxiv_id":"1903.06631","repositories_listed":0,"syntology":null},{"url":null,"slug":"reconstruction-of-3-d-atomic-distortions-from","title":"Reconstruction of 3-D Atomic Distortions from Electron Microscopy with Deep Learning","date":"2019-02-19","arxiv_id":"1902.06876","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-the-memory-wall-a-case-for-memory","title":"Beyond the Memory Wall: A Case for Memory-centric HPC System for Deep Learning","date":"2019-02-18","arxiv_id":"1902.06468","repositories_listed":0,"syntology":null},{"url":null,"slug":"classifying-textual-data-shallow-deep-and","title":"Classifying textual data: shallow, deep and ensemble methods","date":"2019-02-18","arxiv_id":"1902.07068","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-autoencoder-for","title":"An Adaptive Deep Learning Algorithm Based Autoencoder for Interference Channels","date":"2019-02-18","arxiv_id":"1902.06841","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-sub-meter-level-indoor-localization-a","title":"Robust Sub-meter Level Indoor Localization - A Logistic Regression Approach","date":"2019-02-17","arxiv_id":"1902.06226","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-improved-testing-for-deep-learning","title":"Towards Improved Testing For Deep Learning","date":"2019-02-17","arxiv_id":"1902.06320","repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigation-of-adversarial-examples-in-rf-deep","title":"Mitigation of Adversarial Examples in RF Deep Classifiers Utilizing AutoEncoder Pre-training","date":"2019-02-16","arxiv_id":"1902.08034","repositories_listed":0,"syntology":null},{"url":null,"slug":"skin-lesion-segmentation-and-classification","title":"Towards Automated Melanoma Detection with Deep Learning: Data Purification and Augmentation","date":"2019-02-16","arxiv_id":"1902.06061","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-deep-learning-of-gmms","title":"Efficient Deep Learning of GMMs","date":"2019-02-15","arxiv_id":"1902.05707","repositories_listed":0,"syntology":null},{"url":null,"slug":"going-deep-in-medical-image-analysis-concepts","title":"Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions","date":"2019-02-15","arxiv_id":"1902.05655","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-the-circuit-deobfuscating-runtime","title":"Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning","date":"2019-02-14","arxiv_id":"1902.05357","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-network-compression-using","title":"Effective Network Compression Using Simulation-Guided Iterative Pruning","date":"2019-02-12","arxiv_id":"1902.04224","repositories_listed":0,"syntology":null},{"url":null,"slug":"verification-code-recognition-based-on-active","title":"Verification Code Recognition Based on Active and Deep Learning","date":"2019-02-12","arxiv_id":"1902.04401","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-methods-for-event-verification","title":"Deep Learning Methods for Event Verification and Image Repurposing Detection","date":"2019-02-11","arxiv_id":"1902.04038","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-generative-deep-learning-for","title":"Probabilistic Generative Deep Learning for Molecular Design","date":"2019-02-11","arxiv_id":"1902.05148","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-and-face-recognition-the-state","title":"Deep learning and face recognition: the state of the art","date":"2019-02-10","arxiv_id":"1902.03524","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-deep-image-clustering-with-spatial","title":"Improving Deep Image Clustering With Spatial Transformer Layers","date":"2019-02-09","arxiv_id":"1902.05401","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-initialization-when-your-network","title":"On the security relevance of weights in deep learning","date":"2019-02-08","arxiv_id":"1902.03020","repositories_listed":0,"syntology":null},{"url":null,"slug":"software-defined-fpga-accelerator-design-for","title":"Software-Defined FPGA Accelerator Design for Mobile Deep Learning Applications","date":"2019-02-08","arxiv_id":"1902.03192","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-cost-measurement-of-industrial-shock","title":"Low-cost Measurement of Industrial Shock Signals via Deep Learning Calibration","date":"2019-02-07","arxiv_id":"1902.02829","repositories_listed":0,"syntology":null},{"url":null,"slug":"disguised-nets-image-disguising-for-privacy","title":"Disguised-Nets: Image Disguising for Privacy-preserving Outsourced Deep Learning","date":"2019-02-05","arxiv_id":"1902.01878","repositories_listed":0,"syntology":null},{"url":null,"slug":"technical-considerations-for-semantic","title":"Technical Considerations for Semantic Segmentation in MRI using Convolutional Neural Networks","date":"2019-02-05","arxiv_id":"1902.01977","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-solutions-for-tandem-x-based","title":"Deep Learning Solutions for TanDEM-X-based Forest Classification","date":"2019-02-01","arxiv_id":"1902.00274","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-rationalizations-in-deep-reinforcement","title":"Visual Rationalizations in Deep Reinforcement Learning for Atari Games","date":"2019-02-01","arxiv_id":"1902.00566","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-modality-ct-mri-prior-augmented-deep","title":"Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets","date":"2019-01-31","arxiv_id":"1901.11369","repositories_listed":0,"syntology":null}],"record_sha256":"c42cb18aaf1a206fe698a02bb30dd5c842c08844f27bbd3c332fd82003a0fb2f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}