{"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/73","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":73,"pages_in_order":129,"rows_per_page":100,"rows":[7201,7300],"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/72","next":"/task/classification-1/papers/74","papers":[{"url":null,"slug":"3n-gan-semi-supervised-classification-of-x","title":"3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework","date":"2021-09-22","arxiv_id":"2109.13862","repositories_listed":0,"syntology":null},{"url":null,"slug":"bfclass-a-backdoor-free-text-classification","title":"BFClass: A Backdoor-free Text Classification Framework","date":"2021-09-22","arxiv_id":"2109.10855","repositories_listed":0,"syntology":null},{"url":null,"slug":"coarse2fine-fine-grained-text-classification","title":"Coarse2Fine: Fine-grained Text Classification on Coarsely-grained Annotated Data","date":"2021-09-22","arxiv_id":"2109.10856","repositories_listed":0,"syntology":null},{"url":null,"slug":"sharp-analysis-of-random-fourier-features-in","title":"Sharp Analysis of Random Fourier Features in Classification","date":"2021-09-22","arxiv_id":"2109.10623","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-with-nearest-disjoint","title":"Classification with Nearest Disjoint Centroids","date":"2021-09-21","arxiv_id":"2109.10436","repositories_listed":0,"syntology":null},{"url":null,"slug":"early-and-revocable-time-series","title":"Early and Revocable Time Series Classification","date":"2021-09-21","arxiv_id":"2109.10285","repositories_listed":0,"syntology":null},{"url":null,"slug":"introduce-the-result-into-self-attention","title":"Introduce the Result Into Self-Attention","date":"2021-09-21","arxiv_id":"2109.13860","repositories_listed":0,"syntology":null},{"url":null,"slug":"signal-classification-using-smooth","title":"Signal Classification using Smooth Coefficients of Multiple wavelets","date":"2021-09-21","arxiv_id":"2109.09988","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-the-classification-of-error-related","title":"Towards the Classification of Error-Related Potentials using Riemannian Geometry","date":"2021-09-21","arxiv_id":"2109.13085","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-convolutional-neural-networks-by","title":"Explaining Convolutional Neural Networks by Tagging Filters","date":"2021-09-20","arxiv_id":"2109.09389","repositories_listed":0,"syntology":null},{"url":null,"slug":"class-incremental-learning-for-video-action","title":"Class incremental learning for video action classification","date":"2021-09-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ensemble-learning-using-error-correcting","title":"Ensemble Learning using Error Correcting Output Codes: New Classification Error Bounds","date":"2021-09-18","arxiv_id":"2109.08967","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-classification-current-landscape","title":"Multimodal Classification: Current Landscape, Taxonomy and Future Directions","date":"2021-09-18","arxiv_id":"2109.09020","repositories_listed":0,"syntology":null},{"url":null,"slug":"solar-cell-patent-classification-method-based","title":"Solar cell patent classification method based on keyword extraction and deep neural network","date":"2021-09-18","arxiv_id":"2109.08796","repositories_listed":0,"syntology":null},{"url":null,"slug":"violence-detection-in-videos","title":"Violence Detection in Videos","date":"2021-09-18","arxiv_id":"2109.08941","repositories_listed":0,"syntology":null},{"url":null,"slug":"commonsense-knowledge-augmented-pretrained","title":"Commonsense Knowledge-Augmented Pretrained Language Models for Causal Reasoning Classification","date":"2021-09-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-few-shot-intent","title":"Semi-Supervised Few-Shot Intent Classification and Slot Filling","date":"2021-09-17","arxiv_id":"2109.08754","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-relation-classification-as-two-way","title":"Supervised Relation Classification as Two-way Span-Prediction","date":"2021-09-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-comprehensive-patent-approval","title":"Towards Comprehensive Patent Approval Predictions:Beyond Traditional Document Classification","date":"2021-09-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"soft-confusion-matrix-classifier-for-stream","title":"Soft Confusion Matrix Classifier for Stream Classification","date":"2021-09-16","arxiv_id":"2109.07857","repositories_listed":0,"syntology":null},{"url":null,"slug":"weighted-graph-based-signal-temporal-logic","title":"Weighted Graph-Based Signal Temporal Logic Inference Using Neural Networks","date":"2021-09-16","arxiv_id":"2109.08078","repositories_listed":0,"syntology":null},{"url":null,"slug":"dialog-speech-sentiment-classification-for","title":"Dialog speech sentiment classification for imbalanced datasets","date":"2021-09-15","arxiv_id":"2109.07228","repositories_listed":0,"syntology":null},{"url":null,"slug":"introducing-an-abusive-language","title":"Introducing an Abusive Language Classification Framework for Telegram to Investigate the German Hater Community","date":"2021-09-15","arxiv_id":"2109.07346","repositories_listed":0,"syntology":null},{"url":null,"slug":"partner-assisted-learning-for-few-shot-image","title":"Partner-Assisted Learning for Few-Shot Image Classification","date":"2021-09-15","arxiv_id":"2109.07607","repositories_listed":0,"syntology":null},{"url":null,"slug":"expert-knowledge-guided-length-variant","title":"Expert Knowledge-Guided Length-Variant Hierarchical Label Generation for Proposal Classification","date":"2021-09-14","arxiv_id":"2109.06661","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-scale-input-strategies-for","title":"Multi-Scale Input Strategies for Medulloblastoma Tumor Classification using Deep Transfer Learning","date":"2021-09-14","arxiv_id":"2109.06547","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilevel-profiling-of-situation-and","title":"Multilevel profiling of situation and dialogue-based deep networks for movie genre classification using movie trailers","date":"2021-09-14","arxiv_id":"2109.06488","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-class-meta-learning-towards-generalizable","title":"One-Class Meta-Learning: Towards Generalizable Few-Shot Open-Set Classification","date":"2021-09-14","arxiv_id":"2109.06859","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-loss-risks-for-b2b-tendering","title":"Predicting Loss Risks for B2B Tendering Processes","date":"2021-09-14","arxiv_id":"2109.06815","repositories_listed":0,"syntology":null},{"url":null,"slug":"dsnet-a-dual-stream-framework-for-weakly","title":"DSNet: A Dual-Stream Framework for Weakly-Supervised Gigapixel Pathology Image Analysis","date":"2021-09-13","arxiv_id":"2109.05788","repositories_listed":0,"syntology":null},{"url":null,"slug":"effectiveness-of-pre-training-for-few-shot","title":"Effectiveness of Pre-training for Few-shot Intent Classification","date":"2021-09-13","arxiv_id":"2109.05782","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-based-ue-classification-in","title":"Learning-Based UE Classification in Millimeter-Wave Cellular Systems With Mobility","date":"2021-09-13","arxiv_id":"2109.05893","repositories_listed":0,"syntology":null},{"url":null,"slug":"mutual-supervision-for-dense-object-detection","title":"Mutual Supervision for Dense Object Detection","date":"2021-09-13","arxiv_id":"2109.05986","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-emg-signal-classification-via","title":"Real-Time EMG Signal Classification via Recurrent Neural Networks","date":"2021-09-13","arxiv_id":"2109.05674","repositories_listed":0,"syntology":null},{"url":null,"slug":"specified-certainty-classification-with","title":"Specified Certainty Classification, with Application to Read Classification for Reference-Guided Metagenomic Assembly","date":"2021-09-13","arxiv_id":"2109.06677","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-efficiency-of-subclass-knowledge","title":"On the Efficiency of Subclass Knowledge Distillation in Classification Tasks","date":"2021-09-12","arxiv_id":"2109.05587","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-state-capsule-networks-for-text","title":"Dual-State Capsule Networks for Text Classification","date":"2021-09-10","arxiv_id":"2109.04762","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-classification-of-simulated","title":"Unsupervised classification of simulated magnetospheric regions","date":"2021-09-10","arxiv_id":"2109.04916","repositories_listed":0,"syntology":null},{"url":null,"slug":"botspot-deep-learning-classification-of-bot","title":"BotSpot: Deep Learning Classification of Bot Accounts within Twitter","date":"2021-09-08","arxiv_id":"2109.03710","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-optimal-classification-trees-against","title":"Robust Optimal Classification Trees Against Adversarial Examples","date":"2021-09-08","arxiv_id":"2109.03857","repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-based-classification-system-for","title":"BERT based classification system for detecting rumours on Twitter","date":"2021-09-07","arxiv_id":"2109.02975","repositories_listed":0,"syntology":null},{"url":null,"slug":"cim-class-irrelevant-mapping-for-few-shot","title":"CIM: Class-Irrelevant Mapping for Few-Shot Classification","date":"2021-09-07","arxiv_id":"2109.02840","repositories_listed":0,"syntology":null},{"url":null,"slug":"generatively-augmented-neural-network","title":"Generatively Augmented Neural Network Watchdog for Image Classification Networks","date":"2021-09-07","arxiv_id":"2109.06168","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-theoretic-partitioning-of-rnas-and","title":"Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots-II","date":"2021-09-07","arxiv_id":"2109.03236","repositories_listed":0,"syntology":null},{"url":null,"slug":"iccad-special-session-paper-quantum-classical","title":"Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)","date":"2021-09-07","arxiv_id":"2109.02862","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-robustness-with-adversarial","title":"Automated Robustness with Adversarial Training as a Post-Processing Step","date":"2021-09-06","arxiv_id":"2109.02532","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-dietary-assessment-via-integrated","title":"Improving Dietary Assessment Via Integrated Hierarchy Food Classification","date":"2021-09-06","arxiv_id":"2109.02736","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-importance-sampling-for-error","title":"Robust Importance Sampling for Error Estimation in the Context of Optimal Bayesian Transfer Learning","date":"2021-09-05","arxiv_id":"2109.02150","repositories_listed":0,"syntology":null},{"url":"/paper/waste-classification-algorithm","slug":"waste-classification-algorithm","title":"Waste Classification Algorithm","date":"2021-09-04","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-process-name-from-network-data","title":"Predicting Process Name from Network Data","date":"2021-09-03","arxiv_id":"2109.03328","repositories_listed":0,"syntology":null},{"url":null,"slug":"ananet-modeling-association-and-alignment-for","title":"AnANet: Modeling Association and Alignment for Cross-modal Correlation Classification","date":"2021-09-02","arxiv_id":"2109.00693","repositories_listed":0,"syntology":null},{"url":null,"slug":"computing-graph-descriptors-on-edge-streams","title":"Computing Graph Descriptors on Edge Streams","date":"2021-09-02","arxiv_id":"2109.01494","repositories_listed":0,"syntology":null},{"url":null,"slug":"gam-explainable-visual-similarity-and","title":"GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps","date":"2021-09-02","arxiv_id":"2109.00951","repositories_listed":0,"syntology":null},{"url":null,"slug":"impact-of-attention-on-adversarial-robustness","title":"Impact of Attention on Adversarial Robustness of Image Classification Models","date":"2021-09-02","arxiv_id":"2109.00936","repositories_listed":0,"syntology":null},{"url":null,"slug":"mutualgraphnet-a-novel-model-for-motor","title":"MutualGraphNet: A novel model for motor imagery classification","date":"2021-09-02","arxiv_id":"2109.04361","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-classification-for-predicting-multi","title":"Text Classification for Predicting Multi-level Product Categories","date":"2021-09-02","arxiv_id":"2109.01084","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-protection-method-of-trained-cnn-model","title":"A Protection Method of Trained CNN Model Using Feature Maps Transformed With Secret Key From Unauthorized Access","date":"2021-09-01","arxiv_id":"2109.00224","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-study-on-the-joint-impact-of","title":"An Empirical Study on the Joint Impact of Feature Selection and Data Re-sampling on Imbalance Classification","date":"2021-09-01","arxiv_id":"2109.00201","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-deep-learning-methods-to-1","title":"Application of Deep Learning Methods to SNOMED CT Encoding of Clinical Texts: From Data Collection to Extreme Multi-Label Text-Based Classification","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-mix-up-method-in-document","title":"Application of Mix-Up Method in Document Classification Task Using BERT","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-of-code-mixed-text-using","title":"Classification of Code-Mixed Text Using Capsule Networks","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"corpus-creation-and-language-identification","title":"Corpus Creation and Language Identification in Low-Resource Code-Mixed Telugu-English Text","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"detox-at-germeval-2021-toxic-comment","title":"DeTox at GermEval 2021: Toxic Comment Classification","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-multilingual-text-classification","title":"Efficient Multilingual Text Classification for Indian Languages","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"elerrant-automatic-grammatical-error-type","title":"ELERRANT: Automatic Grammatical Error Type Classification for Greek","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-reliability-of-gold-labels-for","title":"Exploring Reliability of Gold Labels for Emotion Detection in Twitter","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-tuning-neural-language-models-for","title":"Fine-tuning Neural Language Models for Multidimensional Opinion Mining of English-Maltese Social Data","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-obtain-reliable-labels-for-mbti","title":"How to Obtain Reliable Labels for MBTI Classification from Texts?","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ircologne-at-germeval-2021-toxicity","title":"IRCologne at GermEval 2021: Toxicity Classification","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-usefulness-of-personality-traits-in","title":"On the Usefulness of Personality Traits in Opinion-oriented Tasks","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"red-a-novel-dataset-for-romanian-emotion","title":"RED: A Novel Dataset for Romanian Emotion Detection from Tweets","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"siamese-networks-for-inference-in-malayalam","title":"Siamese Networks for Inference in Malayalam Language Texts","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"under-bagging-nearest-neighbors-for","title":"Under-bagging Nearest Neighbors for Imbalanced Classification","date":"2021-09-01","arxiv_id":"2109.00531","repositories_listed":0,"syntology":null},{"url":null,"slug":"universitat-regensburg-maxs-at-germeval-2021","title":"Universität Regensburg MaxS at GermEval 2021 Task 1: Synthetic Data in Toxic Comment Classification","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"upappliedcl-at-germeval-2021-identifying-fact","title":"UPAppliedCL at GermEval 2021: Identifying Fact-Claiming and Engaging Facebook Comments Using Transformers","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"wearable-based-classification-of-running","title":"Wearable-based Classification of Running Styles with Deep Learning","date":"2021-09-01","arxiv_id":"2109.00594","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-have-been-learned-what-should-be-learned","title":"What Have Been Learned & What Should Be Learned? An Empirical Study of How to Selectively Augment Text for Classification","date":"2021-09-01","arxiv_id":"2109.00175","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-classes-through-word-attribution","title":"Explaining Classes through Word Attribution","date":"2021-08-31","arxiv_id":"2108.13653","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-interpretable-web-based-glioblastoma","title":"An Interpretable Web-based Glioblastoma Multiforme Prognosis Prediction Tool using Random Forest Model","date":"2021-08-30","arxiv_id":"2108.13039","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-multi-tasking-learning-in-document","title":"Exploring Multi-Tasking Learning in Document Attribute Classification","date":"2021-08-30","arxiv_id":"2108.13382","repositories_listed":0,"syntology":null},{"url":null,"slug":"noisy-labels-for-weakly-supervised-gamma","title":"Noisy Labels for Weakly Supervised Gamma Hadron Classification","date":"2021-08-30","arxiv_id":"2108.13396","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-set-rf-fingerprinting-using-generative","title":"Open Set RF Fingerprinting using Generative Outlier Augmentation","date":"2021-08-30","arxiv_id":"2108.13099","repositories_listed":0,"syntology":null},{"url":null,"slug":"attempt-to-predict-failure-case","title":"Attempt to Predict Failure Case Classification in a Failure Database by using Neural Network Models","date":"2021-08-29","arxiv_id":"2108.12788","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-dive-into-semi-supervised-elbo-for","title":"Deep Dive into Semi-Supervised ELBO for Improving Classification Performance","date":"2021-08-29","arxiv_id":"2108.12734","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-preserving-machine-learning-for","title":"Privacy-preserving Machine Learning for Medical Image Classification","date":"2021-08-29","arxiv_id":"2108.12816","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-quantification-for-multiclass","title":"Uncertainty quantification for multiclass data description","date":"2021-08-29","arxiv_id":"2108.12857","repositories_listed":0,"syntology":null},{"url":"/paper/threshold-pruning-tool-for-densely-connected","slug":"threshold-pruning-tool-for-densely-connected","title":"New Pruning Method Based on DenseNet Network for Image Classification","date":"2021-08-28","arxiv_id":"2108.12604","repositories_listed":0,"syntology":null},{"url":null,"slug":"fractal-measures-of-image-local-features-an","title":"Fractal measures of image local features: an application to texture recognition","date":"2021-08-27","arxiv_id":"2108.12491","repositories_listed":0,"syntology":null},{"url":null,"slug":"visgraphnet-a-complex-network-interpretation","title":"VisGraphNet: a complex network interpretation of convolutional neural features","date":"2021-08-27","arxiv_id":"2108.12490","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-automatic-image-content-retrieval-method","title":"An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences","date":"2021-08-26","arxiv_id":"2108.12068","repositories_listed":0,"syntology":null},{"url":null,"slug":"gene-transformer-transformers-for-the-gene","title":"DeepGene Transformer: Transformer for the gene expression-based classification of cancer subtypes","date":"2021-08-26","arxiv_id":"2108.11833","repositories_listed":0,"syntology":null},{"url":null,"slug":"svm-classifier-on-chip-for-melanoma-detection","title":"SVM Classifier on Chip for Melanoma Detection","date":"2021-08-26","arxiv_id":"2108.11957","repositories_listed":0,"syntology":null},{"url":null,"slug":"cascading-neural-network-methodology-for","title":"Cascading Neural Network Methodology for Artificial Intelligence-Assisted Radiographic Detection and Classification of Lead-Less Implanted Electronic Devices within the Chest","date":"2021-08-25","arxiv_id":"2108.11954","repositories_listed":0,"syntology":null},{"url":null,"slug":"reasoning-about-counterfactuals-and","title":"Reasoning about Counterfactuals and Explanations: Problems, Results and Directions","date":"2021-08-25","arxiv_id":"2108.11004","repositories_listed":0,"syntology":null},{"url":null,"slug":"reconcile-prediction-consistency-for-balanced","title":"Reconcile Prediction Consistency for Balanced Object Detection","date":"2021-08-24","arxiv_id":"2108.10809","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-modulation-classification-using","title":"Automatic Modulation Classification Using Involution Enabled Residual Networks","date":"2021-08-23","arxiv_id":"2108.10001","repositories_listed":0,"syntology":null},{"url":null,"slug":"eeg-based-classification-of-drivers-attention","title":"EEG-based Classification of Drivers Attention using Convolutional Neural Network","date":"2021-08-23","arxiv_id":"2108.10062","repositories_listed":0,"syntology":null},{"url":null,"slug":"fusion-of-evidential-cnn-classifiers-for","title":"Fusion of evidential CNN classifiers for image classification","date":"2021-08-23","arxiv_id":"2108.10233","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-transferable-are-self-supervised-features","title":"How Transferable Are Self-supervised Features in Medical Image Classification Tasks?","date":"2021-08-23","arxiv_id":"2108.10048","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hard-label-black-box-adversarial-attack","title":"A Hard Label Black-box Adversarial Attack Against Graph Neural Networks","date":"2021-08-21","arxiv_id":"2108.09513","repositories_listed":0,"syntology":null}],"record_sha256":"f330161e80cb7c6dc293b6747e23dac8aebee312f6197acc859afc7a74d597f8","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}