{"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/classification-1/papers/109","list_of":"/task/classification-1","task":"Classification","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":109,"pages_in_order":129,"rows_per_page":100,"rows":[10801,10900],"of":12815,"counts":{"archive_papers_tagged":12815,"with_a_code_link":3778,"where_syntology_ran_a_sample":582,"not_listed_spam_title":0,"listed":12815,"listed_where_code_ran":582,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":457,"every_run_a_failure_of_syntologys_instrument":125,"listed_with_a_run_with_no_instrument_failure":457,"listed_every_run_a_failure_of_syntologys_instrument":125,"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/classification-1","prev":"/task/classification-1/papers/108","next":"/task/classification-1/papers/110","papers":[{"url":null,"slug":"noise-resistant-deep-learning-for-object","title":"Noise-resistant Deep Learning for Object Classification in 3D Point Clouds Using a Point Pair Descriptor","date":"2018-04-05","arxiv_id":"1804.02077","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-classification-for-oil","title":"Semi-Supervised Classification for oil reservoir","date":"2018-04-05","arxiv_id":"1804.01675","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-a-classifier-ensemble-for-proactive","title":"Using a Classifier Ensemble for Proactive Quality Monitoring and Control: the impact of the choice of classifiers types, selection criterion, and fusion process","date":"2018-04-05","arxiv_id":"1804.01684","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-based-vision-meets-deep-learning-on","title":"Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars","date":"2018-04-04","arxiv_id":"1804.01310","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-multi-label-classification-a-label","title":"Online Multi-Label Classification: A Label Compression Method","date":"2018-04-04","arxiv_id":"1804.01491","repositories_listed":0,"syntology":null},{"url":null,"slug":"emorl-continuous-acoustic-emotion","title":"EmoRL: Continuous Acoustic Emotion Classification using Deep Reinforcement Learning","date":"2018-04-03","arxiv_id":"1804.04053","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-word-embeddings-into-open","title":"Incorporating Word Embeddings into Open Directory Project based Large-scale Classification","date":"2018-04-03","arxiv_id":"1804.00828","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-scale-spatially-asymmetric","title":"Multi-Scale Spatially-Asymmetric Recalibration for Image Classification","date":"2018-04-03","arxiv_id":"1804.00787","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-spatiotemporal-models-for-robust","title":"Deep Spatiotemporal Models for Robust Proprioceptive Terrain Classification","date":"2018-04-02","arxiv_id":"1804.00736","repositories_listed":0,"syntology":null},{"url":null,"slug":"sampleahead-online-classifier-sampler","title":"SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data","date":"2018-04-01","arxiv_id":"1804.00248","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-depth-question-classification-using","title":"In-depth Question classification using Convolutional Neural Networks","date":"2018-03-31","arxiv_id":"1804.00968","repositories_listed":0,"syntology":null},{"url":null,"slug":"webly-supervised-learning-for-skin-lesion","title":"Webly Supervised Learning for Skin Lesion Classification","date":"2018-03-31","arxiv_id":"1804.00177","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatically-augmenting-an-emotion-dataset","title":"Automatically augmenting an emotion dataset improves classification using audio","date":"2018-03-30","arxiv_id":"1803.11506","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-transfer-convolutional-neural","title":"Hierarchical Transfer Convolutional Neural Networks for Image Classification","date":"2018-03-30","arxiv_id":"1804.00021","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-disease-classification-in","title":"Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion","date":"2018-03-30","arxiv_id":"1803.11550","repositories_listed":0,"syntology":null},{"url":null,"slug":"bag-of-recurrence-patterns-representation-for","title":"Bag of Recurrence Patterns Representation for Time-Series Classification","date":"2018-03-29","arxiv_id":"1803.11111","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-metric-learning-for-supervised","title":"Active Metric Learning for Supervised Classification","date":"2018-03-28","arxiv_id":"1803.10647","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-based-deep-learning-for-classification","title":"Image-based deep learning for classification of noise transients in gravitational wave detectors","date":"2018-03-27","arxiv_id":"1803.09933","repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-developments-from-attribute-profiles","title":"Recent Developments from Attribute Profiles for Remote Sensing Image Classification","date":"2018-03-27","arxiv_id":"1803.10036","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-classification-of-cropping-patterns-based","title":"The Classification of Cropping Patterns Based on Regional Climate Classification Using Decision Tree Approach","date":"2018-03-26","arxiv_id":"1803.11259","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-adversarial-perturbations-with","title":"Detecting Adversarial Perturbations with Saliency","date":"2018-03-23","arxiv_id":"1803.08773","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-deep-context-network-architectures","title":"Learning Deep Context-Network Architectures for Image Annotation","date":"2018-03-23","arxiv_id":"1803.08794","repositories_listed":0,"syntology":null},{"url":null,"slug":"entrenamiento-de-una-red-neuronal-para-el","title":"Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad","date":"2018-03-22","arxiv_id":"1804.00508","repositories_listed":0,"syntology":null},{"url":null,"slug":"corpus-statistics-in-text-classification-of","title":"Corpus Statistics in Text Classification of Online Data","date":"2018-03-16","arxiv_id":"1803.06390","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancing-connectionist-temporal","title":"Advancing Connectionist Temporal Classification With Attention Modeling","date":"2018-03-15","arxiv_id":"1803.05563","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-agnostic-private-learning-via-stability","title":"Model-Agnostic Private Learning via Stability","date":"2018-03-14","arxiv_id":"1803.05101","repositories_listed":0,"syntology":null},{"url":"/paper/rotation-sensitive-regression-for-oriented","slug":"rotation-sensitive-regression-for-oriented","title":"Rotation-Sensitive Regression for Oriented Scene Text Detection","date":"2018-03-14","arxiv_id":"1803.05265","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-technique-based-on-chaos-for-brain-computer","title":"A Technique Based on Chaos for Brain Computer Interfacing","date":"2018-03-13","arxiv_id":"1803.05500","repositories_listed":0,"syntology":null},{"url":null,"slug":"protein-mutation-stability-ternary","title":"Protein Mutation Stability Ternary Classification using Neural Networks and Rigidity Analysis","date":"2018-03-13","arxiv_id":"1803.04659","repositories_listed":0,"syntology":null},{"url":null,"slug":"saf-bage-salient-approach-for-facial-soft","title":"SAF- BAGE: Salient Approach for Facial Soft-Biometric Classification - Age, Gender, and Facial Expression","date":"2018-03-13","arxiv_id":"1803.05719","repositories_listed":0,"syntology":null},{"url":null,"slug":"innovative-texture-database-collecting","title":"Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns,and K-means Clustering","date":"2018-03-12","arxiv_id":"1803.04125","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-dictionary-learning-a-parametric-network","title":"Deep Dictionary Learning: A PARametric NETwork Approach","date":"2018-03-11","arxiv_id":"1803.04022","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-integrated-inverse-space-sparse","title":"An Integrated Inverse Space Sparse Representation Framework for Tumor Classification","date":"2018-03-09","arxiv_id":"1803.03562","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparison-of-deep-learning-approaches-for","title":"Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification","date":"2018-03-06","arxiv_id":"1803.02315","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparison-of-various-image-fusion-methods","title":"Comparison of various image fusion methods for impervious surface classification from VNREDSat-1","date":"2018-03-06","arxiv_id":"1803.02326","repositories_listed":0,"syntology":null},{"url":null,"slug":"2b3c-2-box-3-crop-of-facial-image-for-gender","title":"2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks","date":"2018-03-05","arxiv_id":"1803.02181","repositories_listed":0,"syntology":null},{"url":null,"slug":"style-memory-making-a-classifier-network","title":"Style Memory: Making a Classifier Network Generative","date":"2018-03-05","arxiv_id":"1803.01900","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-based-grasp-detection-using","title":"Classification based Grasp Detection using Spatial Transformer Network","date":"2018-03-04","arxiv_id":"1803.01356","repositories_listed":0,"syntology":null},{"url":null,"slug":"gan-based-synthetic-medical-image","title":"GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification","date":"2018-03-03","arxiv_id":"1803.01229","repositories_listed":0,"syntology":null},{"url":null,"slug":"age-group-classification-with-speech-and","title":"Age Group Classification with Speech and Metadata Multimodality Fusion","date":"2018-03-02","arxiv_id":"1803.00721","repositories_listed":0,"syntology":null},{"url":null,"slug":"lexico-acoustic-neural-based-models-for","title":"Lexico-acoustic Neural-based Models for Dialog Act Classification","date":"2018-03-02","arxiv_id":"1803.00831","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-distance-based-classifier-with","title":"Quantum distance-based classifier with constant size memory, distributed knowledge and state recycling","date":"2018-03-02","arxiv_id":"1803.00853","repositories_listed":0,"syntology":null},{"url":null,"slug":"facial-expression-recognition-based-on","title":"Facial Expression Recognition Based on Complexity Perception Classification Algorithm","date":"2018-03-01","arxiv_id":"1803.00185","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-based-clustering-and-classification-of","title":"Model-Based Clustering and Classification of Functional Data","date":"2018-03-01","arxiv_id":"1803.00276","repositories_listed":0,"syntology":null},{"url":null,"slug":"tongue-image-constitution-recognition-based","title":"Tongue image constitution recognition based on Complexity Perception method","date":"2018-03-01","arxiv_id":"1803.00219","repositories_listed":0,"syntology":null},{"url":null,"slug":"constrained-classification-and-ranking-via","title":"Constrained Classification and Ranking via Quantiles","date":"2018-02-28","arxiv_id":"1803.00067","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-discriminative-multilevel-structured","title":"Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification","date":"2018-02-28","arxiv_id":"1802.10497","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-shape-analysis-in-a-bayesian","title":"Statistical shape analysis in a Bayesian framework for shapes in two and three dimensions","date":"2018-02-28","arxiv_id":"1802.10570","repositories_listed":0,"syntology":null},{"url":null,"slug":"brain-tumor-type-classification-via-capsule","title":"Brain Tumor Type Classification via Capsule Networks","date":"2018-02-27","arxiv_id":"1802.10200","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai4ai-quantitative-methods-for-classifying","title":"AI4AI: Quantitative Methods for Classifying Host Species from Avian Influenza DNA Sequence","date":"2018-02-26","arxiv_id":"1802.09197","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-of-breast-cancer-histology-1","title":"Classification of breast cancer histology images using transfer learning","date":"2018-02-26","arxiv_id":"1802.09424","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-instance-classification-using-street","title":"Building Instance Classification Using Street View Images","date":"2018-02-25","arxiv_id":"1802.09026","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiclass-common-spatial-pattern-for-eeg","title":"Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier","date":"2018-02-25","arxiv_id":"1802.09046","repositories_listed":0,"syntology":null},{"url":null,"slug":"ohiostate-at-semeval-2018-task-7-exploiting","title":"OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers using Piecewise Convolutional Neural Networks","date":"2018-02-25","arxiv_id":"1802.08949","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-coniferdeciduous","title":"Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees","date":"2018-02-24","arxiv_id":"1802.08872","repositories_listed":0,"syntology":null},{"url":null,"slug":"coloring-black-boxes-visualization-of-neural","title":"Coloring black boxes: visualization of neural network decisions","date":"2018-02-23","arxiv_id":"1802.08478","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-image-conditioned-label-space-for","title":"Learning Image Conditioned Label Space for Multilabel Classification","date":"2018-02-21","arxiv_id":"1802.07460","repositories_listed":0,"syntology":null},{"url":null,"slug":"elasticpath2path-automated-morphological","title":"ElasticPath2Path: Automated morphological classification of neurons by elastic path matching","date":"2018-02-20","arxiv_id":"1802.06913","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-the-loss-surface-of-neural","title":"Understanding the Loss Surface of Neural Networks for Binary Classification","date":"2018-02-19","arxiv_id":"1803.00909","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-generative-modeling-approach-to-limited","title":"A Generative Modeling Approach to Limited Channel ECG Classification","date":"2018-02-18","arxiv_id":"1802.06458","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayes-optimal-hierarchical-classification","title":"Bayes-optimal Hierarchical Classification over Asymmetric Tree-Distance Loss","date":"2018-02-17","arxiv_id":"1802.06771","repositories_listed":0,"syntology":null},{"url":null,"slug":"implementation-of-neural-network-and-feature","title":"Implementation of Neural Network and feature extraction to classify ECG signals","date":"2018-02-17","arxiv_id":"1802.06288","repositories_listed":0,"syntology":null},{"url":null,"slug":"tabvec-table-vectors-for-classification-of","title":"TabVec: Table Vectors for Classification of Web Tables","date":"2018-02-17","arxiv_id":"1802.06290","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-dataset-for-visual-objects","title":"Image Dataset for Visual Objects Classification in 3D Printing","date":"2018-02-15","arxiv_id":"1803.00391","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributional-term-set-expansion","title":"Distributional Term Set Expansion","date":"2018-02-14","arxiv_id":"1802.05014","repositories_listed":0,"syntology":null},{"url":null,"slug":"prophit-causal-inverse-classification-for","title":"Prophit: Causal inverse classification for multiple continuously valued treatment policies","date":"2018-02-14","arxiv_id":"1802.04918","repositories_listed":0,"syntology":null},{"url":null,"slug":"texture-classification-in-extreme-scale","title":"Texture Classification in Extreme Scale Variations using GANet","date":"2018-02-13","arxiv_id":"1802.04441","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-generation-of-language-independent","title":"Automatic Generation of Language-Independent Features for Cross-Lingual Classification","date":"2018-02-12","arxiv_id":"1802.04028","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridge-type-classification-supervised","title":"Bridge type classification: supervised learning on a modified NBI dataset","date":"2018-02-12","arxiv_id":"1803.04478","repositories_listed":0,"syntology":null},{"url":null,"slug":"context-aware-learning-using-transferable","title":"Context-Aware Learning using Transferable Features for Classification of Breast Cancer Histology Images","date":"2018-02-12","arxiv_id":"1803.00386","repositories_listed":0,"syntology":null},{"url":null,"slug":"email-classification-into-relevant-category","title":"Email Classification into Relevant Category Using Neural Networks","date":"2018-02-12","arxiv_id":"1802.03971","repositories_listed":0,"syntology":null},{"url":null,"slug":"lightweight-classification-of-iot-malware","title":"Lightweight Classification of IoT Malware based on Image Recognition","date":"2018-02-11","arxiv_id":"1802.03714","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-classification-of-dermatological","title":"Supervised classification of Dermatological diseases by Deep learning","date":"2018-02-11","arxiv_id":"1802.03752","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-convolutional-networks-with","title":"Understanding Convolutional Networks with APPLE : Automatic Patch Pattern Labeling for Explanation","date":"2018-02-11","arxiv_id":"1802.03675","repositories_listed":0,"syntology":null},{"url":null,"slug":"document-classification-using-distributed","title":"Document Classification Using Distributed Machine Learning","date":"2018-02-10","arxiv_id":"1802.03597","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-distributed-svrg-for-high-dimensional","title":"Feature-Distributed SVRG for High-Dimensional Linear Classification","date":"2018-02-10","arxiv_id":"1802.03604","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-networks-and-1","title":"Generative Adversarial Networks and Probabilistic Graph Models for Hyperspectral Image Classification","date":"2018-02-10","arxiv_id":"1802.03495","repositories_listed":0,"syntology":null},{"url":null,"slug":"textzoo-a-new-benchmark-for-reconsidering","title":"TextZoo, a New Benchmark for Reconsidering Text Classification","date":"2018-02-10","arxiv_id":"1802.03656","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-local-metrics-and-influential","title":"Learning Local Metrics and Influential Regions for Classification","date":"2018-02-09","arxiv_id":"1802.03452","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-classification-of-galaxies-i-ica","title":"Unsupervised Classification of Galaxies. I. ICA feature selection","date":"2018-02-08","arxiv_id":"1802.02856","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-of-things-in-dbpedia-using","title":"Classification of Things in DBpedia using Deep Neural Networks","date":"2018-02-07","arxiv_id":"1802.02528","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-versus-wide-convolutional-neural","title":"Deep Versus Wide Convolutional Neural Networks for Object Recognition on Neuromorphic System","date":"2018-02-07","arxiv_id":"1802.02608","repositories_listed":0,"syntology":null},{"url":null,"slug":"neyman-pearson-classification-parametrics-and","title":"Neyman-Pearson classification: parametrics and sample size requirement","date":"2018-02-07","arxiv_id":"1802.02557","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-large-scale-multi-modal","title":"Efficient Large-Scale Multi-Modal Classification","date":"2018-02-06","arxiv_id":"1802.02892","repositories_listed":0,"syntology":null},{"url":"/paper/multi-temporal-land-cover-classification-with","slug":"multi-temporal-land-cover-classification-with","title":"Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders","date":"2018-02-06","arxiv_id":"1802.02080","repositories_listed":0,"syntology":null},{"url":null,"slug":"ensembling-neural-networks-for-digital","title":"Ensembling Neural Networks for Digital Pathology Images Classification and Segmentation","date":"2018-02-03","arxiv_id":"1802.00947","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-binary-neural-network-for-multi-label","title":"Joint Binary Neural Network for Multi-label Learning with Applications to Emotion Classification","date":"2018-02-03","arxiv_id":"1802.00891","repositories_listed":0,"syntology":null},{"url":null,"slug":"causal-learning-and-explanation-of-deep","title":"Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations","date":"2018-02-02","arxiv_id":"1802.00541","repositories_listed":0,"syntology":null},{"url":null,"slug":"complex-network-classification-with","title":"Complex Network Classification with Convolutional Neural Network","date":"2018-02-02","arxiv_id":"1802.00539","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-cnn-for-hyperspectral-image","title":"Cross-domain CNN for Hyperspectral Image Classification","date":"2018-01-31","arxiv_id":"1802.00093","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-compression-for-faster-structural","title":"Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography","date":"2018-01-31","arxiv_id":"1801.10597","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-detection-in-videos-by-short-and-long","title":"Object Detection in Videos by Short and Long Range Object Linking","date":"2018-01-30","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-of-classification-ability-of","title":"Robustness of classification ability of spiking neural networks","date":"2018-01-30","arxiv_id":"1801.09827","repositories_listed":0,"syntology":null},{"url":null,"slug":"approximate-vanishing-ideal-via-data-knotting","title":"Approximate Vanishing Ideal via Data Knotting","date":"2018-01-29","arxiv_id":"1801.09367","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-rapidly-deployable-classification-system","title":"A Rapidly Deployable Classification System using Visual Data for the Application of Precision Weed Management","date":"2018-01-25","arxiv_id":"1801.08613","repositories_listed":0,"syntology":null},{"url":null,"slug":"deeppap-deep-convolutional-networks-for","title":"DeepPap: Deep Convolutional Networks for Cervical Cell Classification","date":"2018-01-25","arxiv_id":"1801.08616","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-in-apogee-unsupervised","title":"Machine learning in APOGEE: Unsupervised spectral classification with $K$-means","date":"2018-01-24","arxiv_id":"1801.07912","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-classification-refinement-strategy-for","title":"A Classification Refinement Strategy for Semantic Segmentation","date":"2018-01-23","arxiv_id":"1801.07674","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecg-signal-preprocessing-and-svm-classifier","title":"ECG Signal Preprocessing and SVM Classifier-Based Abnormality Detection in Remote Healthcare Applications","date":"2018-01-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"time-series-kernel-similarities-for","title":"Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs","date":"2018-01-21","arxiv_id":"1801.06845","repositories_listed":0,"syntology":null}],"record_sha256":"cac35faf8ee956b64a26267819aa0deda4c1695b5e99ec5912ed5af959c8a408","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}