{"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/62","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":62,"pages_in_order":129,"rows_per_page":100,"rows":[6101,6200],"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/61","next":"/task/classification-1/papers/63","papers":[{"url":null,"slug":"improved-zero-shot-audio-tagging","title":"Improved Zero-Shot Audio Tagging & Classification with Patchout Spectrogram Transformers","date":"2022-08-24","arxiv_id":"2208.11402","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-evolutionary-approach-for-creating-of","title":"An Evolutionary Approach for Creating of Diverse Classifier Ensembles","date":"2022-08-23","arxiv_id":"2208.10996","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-neural-networks-with-a","title":"Convolutional Neural Networks with A Topographic Representation Module for EEG-Based Brain-Computer Interfaces","date":"2022-08-23","arxiv_id":"2208.10708","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-lapse-image-classification-using-a","title":"Time-lapse image classification using a diffractive neural network","date":"2022-08-23","arxiv_id":"2208.10802","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecu-identification-using-neural-network","title":"ECU Identification using Neural Network Classification and Hyperparameter Tuning","date":"2022-08-22","arxiv_id":"2208.10651","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-complexity-classification-approach-for","title":"Low Complexity Classification Approach for Faster-than-Nyquist (FTN) Signalling Detection","date":"2022-08-22","arxiv_id":"2208.10637","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilayer-deep-feature-extraction-for-visual","title":"Multilayer deep feature extraction for visual texture recognition","date":"2022-08-22","arxiv_id":"2208.10044","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-tagging-of-knowledge-points-for-k12","title":"Automatic tagging of knowledge points for K12 math problems","date":"2022-08-21","arxiv_id":"2208.09867","repositories_listed":0,"syntology":null},{"url":"/paper/a-dual-modality-approach-for-zero-shot-multi","slug":"a-dual-modality-approach-for-zero-shot-multi","title":"Open Vocabulary Multi-Label Classification with Dual-Modal Decoder on Aligned Visual-Textual Features","date":"2022-08-19","arxiv_id":"2208.09562","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-performance-metric-elicitation","title":"Classification Performance Metric Elicitation and its Applications","date":"2022-08-19","arxiv_id":"2208.09142","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-image-classification-with-token","title":"Improved Image Classification with Token Fusion","date":"2022-08-19","arxiv_id":"2208.09183","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-the-knowledge-in-a-dnn-to-explain","title":"Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification","date":"2022-08-18","arxiv_id":"2208.08741","repositories_listed":0,"syntology":null},{"url":null,"slug":"tree-species-classification-from","title":"Tree species classification from hyperspectral data using graph-regularized neural networks","date":"2022-08-18","arxiv_id":"2208.08675","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-few-shot-classification-via-2","title":"Cross-Domain Few-Shot Classification via Inter-Source Stylization","date":"2022-08-17","arxiv_id":"2208.08015","repositories_listed":0,"syntology":null},{"url":"/paper/deep-generative-views-to-mitigate-gender","slug":"deep-generative-views-to-mitigate-gender","title":"Deep Generative Views to Mitigate Gender Classification Bias Across Gender-Race Groups","date":"2022-08-17","arxiv_id":"2208.08382","repositories_listed":0,"syntology":null},{"url":null,"slug":"early-heart-disease-prediction-using-hybrid","title":"Heart Disease Detection using Quantum Computing and Partitioned Random Forest Methods","date":"2022-08-17","arxiv_id":"2208.08882","repositories_listed":0,"syntology":null},{"url":null,"slug":"leukocyte-classification-using-multimodal","title":"Leukocyte Classification using Multimodal Architecture Enhanced by Knowledge Distillation","date":"2022-08-17","arxiv_id":"2208.08331","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-long-tailed-recognition-in-a-dynamic","title":"Open Long-Tailed Recognition in a Dynamic World","date":"2022-08-17","arxiv_id":"2208.08349","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-anomaly-detection-based-on","title":"Semi-Supervised Anomaly Detection Based on Quadratic Multiform Separation","date":"2022-08-17","arxiv_id":"2208.08265","repositories_listed":0,"syntology":null},{"url":null,"slug":"bertifying-sinhala-a-comprehensive-analysis","title":"BERTifying Sinhala -- A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classification","date":"2022-08-16","arxiv_id":"2208.07864","repositories_listed":0,"syntology":null},{"url":null,"slug":"fold-se-scalable-explainable-ai","title":"FOLD-SE: An Efficient Rule-based Machine Learning Algorithm with Scalable Explainability","date":"2022-08-16","arxiv_id":"2208.07912","repositories_listed":0,"syntology":null},{"url":null,"slug":"acceleration-of-subspace-learning-machine-via","title":"Acceleration of Subspace Learning Machine via Particle Swarm Optimization and Parallel Processing","date":"2022-08-15","arxiv_id":"2208.07023","repositories_listed":0,"syntology":null},{"url":null,"slug":"preventing-deterioration-of-classification","title":"Preventing Deterioration of Classification Accuracy in Predictive Coding Networks","date":"2022-08-15","arxiv_id":"2208.07114","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-time-attacks-against-k-nearest","title":"Training-Time Attacks against k-Nearest Neighbors","date":"2022-08-15","arxiv_id":"2208.07272","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-skull-fractures-via-cnn-with","title":"Predicting skull fractures via CNN with classification algorithms","date":"2022-08-14","arxiv_id":"2208.06756","repositories_listed":0,"syntology":null},{"url":null,"slug":"incoporating-weighted-board-learning-system","title":"Incoporating Weighted Board Learning System for Accurate Occupational Pneumoconiosis Staging","date":"2022-08-13","arxiv_id":"2208.06607","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-adversarial-attacks-on-graph","title":"Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification","date":"2022-08-13","arxiv_id":"2208.06651","repositories_listed":0,"syntology":null},{"url":null,"slug":"shifted-windows-transformers-for-medical","title":"Shifted Windows Transformers for Medical Image Quality Assessment","date":"2022-08-11","arxiv_id":"2208.06034","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilayer-fisher-extreme-learning-machine","title":"Multilayer Fisher extreme learning machine for classification","date":"2022-08-10","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"trustworthy-visual-analytics-in-clinical-gait","title":"Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy","date":"2022-08-10","arxiv_id":"2208.05232","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficientnet-for-brain-lesion-classification","title":"EfficientNet for Brain-Lesion classification","date":"2022-08-09","arxiv_id":"2208.04616","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-prediction-of-qcodes-for-notams","title":"Explainable prediction of Qcodes for NOTAMs using column generation","date":"2022-08-09","arxiv_id":"2208.04955","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-label-continual-learning-framework-to","title":"A Multi-label Continual Learning Framework to Scale Deep Learning Approaches for Packaging Equipment Monitoring","date":"2022-08-08","arxiv_id":"2208.04227","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-example-of-use-of-variational-methods-in","title":"An example of use of Variational Methods in Quantum Machine Learning","date":"2022-08-07","arxiv_id":"2208.04316","repositories_listed":0,"syntology":null},{"url":null,"slug":"continual-learning-for-tumor-classification","title":"Continual Learning for Tumor Classification in Histopathology Images","date":"2022-08-07","arxiv_id":"2208.03609","repositories_listed":0,"syntology":null},{"url":null,"slug":"construction-of-english-resume-corpus-and","title":"Construction of English Resume Corpus and Test with Pre-trained Language Models","date":"2022-08-05","arxiv_id":"2208.03219","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-blending-for-text-classification","title":"Model Blending for Text Classification","date":"2022-08-05","arxiv_id":"2208.02819","repositories_listed":0,"syntology":null},{"url":null,"slug":"mordeephy-face-morphing-detection-via-fused","title":"MorDeephy: Face Morphing Detection Via Fused Classification","date":"2022-08-05","arxiv_id":"2208.03110","repositories_listed":0,"syntology":null},{"url":null,"slug":"radtex-learning-efficient-radiograph","title":"RadTex: Learning Efficient Radiograph Representations from Text Reports","date":"2022-08-05","arxiv_id":"2208.03218","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-balanced-distillation-for-object","title":"Task-Balanced Distillation for Object Detection","date":"2022-08-05","arxiv_id":"2208.03006","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-frequency-distributions-of-heart-sound","title":"Time-Frequency Distributions of Heart Sound Signals: A Comparative Study using Convolutional Neural Networks","date":"2022-08-05","arxiv_id":"2208.03128","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-automated-classification-and","title":"A Novel Automated Classification and Segmentation for COVID-19 using 3D CT Scans","date":"2022-08-04","arxiv_id":"2208.02910","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-preserving-image-classification-using-2","title":"Privacy-Preserving Image Classification Using ConvMixer with Adaptive Permutation Matrix","date":"2022-08-04","arxiv_id":"2208.02556","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmentation-learning-for-semi-supervised","title":"Augmentation Learning for Semi-Supervised Classification","date":"2022-08-03","arxiv_id":"2208.01956","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiclass-asma-vs-targeted-pgd-attack-in","title":"Multiclass ASMA vs Targeted PGD Attack in Image Segmentation","date":"2022-08-03","arxiv_id":"2208.01844","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-node-at-a-time-node-level-network","title":"One Node at a Time: Node-Level Network Classification","date":"2022-08-03","arxiv_id":"2208.02162","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-attention-localization-sal","title":"Statistical Attention Localization (SAL): Methodology and Application to Object Classification","date":"2022-08-03","arxiv_id":"2208.01823","repositories_listed":0,"syntology":null},{"url":"/paper/beike-nlp-at-semeval-2022-task-4-prompt-based-1","slug":"beike-nlp-at-semeval-2022-task-4-prompt-based-1","title":"BEIKE NLP at SemEval-2022 Task 4: Prompt-Based Paragraph Classification for Patronizing and Condescending Language Detection","date":"2022-08-02","arxiv_id":"2208.01312","repositories_listed":0,"syntology":null},{"url":null,"slug":"binary-classification-with-positive-labeling","title":"Binary Classification with Positive Labeling Sources","date":"2022-08-02","arxiv_id":"2208.01704","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-complexity-cnns-for-acoustic-scene-1","title":"Low-complexity CNNs for Acoustic Scene Classification","date":"2022-08-02","arxiv_id":"2208.01555","repositories_listed":0,"syntology":null},{"url":null,"slug":"mt-snn-spiking-neural-network-that-enables","title":"MT-SNN: Spiking Neural Network that Enables Single-Tasking of Multiple Tasks","date":"2022-08-02","arxiv_id":"2208.01522","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-gain-sampling-for-active-learning","title":"Information Gain Sampling for Active Learning in Medical Image Classification","date":"2022-08-01","arxiv_id":"2208.00974","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-time-series-clustering-using","title":"Interpretable Time Series Clustering Using Local Explanations","date":"2022-08-01","arxiv_id":"2208.01152","repositories_listed":0,"syntology":null},{"url":null,"slug":"factorizable-joint-shift-in-multinomial","title":"Factorizable Joint Shift in Multinomial Classification","date":"2022-07-29","arxiv_id":"2207.14514","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-augmentation-for-satellite-images","title":"Image Augmentation for Satellite Images","date":"2022-07-29","arxiv_id":"2207.14580","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-classification-of-nanoparticles","title":"Automated Classification of Nanoparticles with Various Ultrastructures and Sizes","date":"2022-07-28","arxiv_id":"2207.14023","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-layer-representation-learning-for-1","title":"Multi-layer Representation Learning for Robust OOD Image Classification","date":"2022-07-27","arxiv_id":"2207.13678","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-intent-classification-and-slot","title":"A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog","date":"2022-07-26","arxiv_id":"2207.13211","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-interpretable-filters-to-predictions-of","title":"From Interpretable Filters to Predictions of Convolutional Neural Networks with Explainable Artificial Intelligence","date":"2022-07-26","arxiv_id":"2207.12958","repositories_listed":0,"syntology":null},{"url":null,"slug":"infant-movement-classification-through","title":"Infant movement classification through pressure distribution analysis","date":"2022-07-26","arxiv_id":"2208.00884","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-bert-fails-the-limits-of-ehr","title":"When BERT Fails -- The Limits of EHR Classification","date":"2022-07-26","arxiv_id":"2208.10245","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-encryption-method-of-convmixer-models","title":"An Encryption Method of ConvMixer Models without Performance Degradation","date":"2022-07-25","arxiv_id":"2207.11939","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-knowledge-augmented-meta-learning","title":"Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification","date":"2022-07-25","arxiv_id":"2207.12346","repositories_listed":0,"syntology":null},{"url":null,"slug":"arbitrary-style-transfer-with-structure","title":"Arbitrary Style Transfer with Structure Enhancement by Combining the Global and Local Loss","date":"2022-07-23","arxiv_id":"2207.11438","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmented-bilinear-network-for-incremental","title":"Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification","date":"2022-07-23","arxiv_id":"2207.11577","repositories_listed":0,"syntology":null},{"url":null,"slug":"better-reasoning-behind-classification","title":"Better Reasoning Behind Classification Predictions with BERT for Fake News Detection","date":"2022-07-23","arxiv_id":"2207.11562","repositories_listed":0,"syntology":null},{"url":null,"slug":"fastatdc-fast-anomalous-trajectory-detection","title":"FastATDC: Fast Anomalous Trajectory Detection and Classification","date":"2022-07-23","arxiv_id":"2207.11541","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-complexity-cnns-for-acoustic-scene","title":"Low-complexity CNNs for Acoustic Scene Classification","date":"2022-07-23","arxiv_id":"2207.11529","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-via-score-based-generative","title":"Classification via score-based generative modelling","date":"2022-07-22","arxiv_id":"2207.11091","repositories_listed":0,"syntology":null},{"url":null,"slug":"comment-on-on-the-extraction-of-purely-motor","title":"Comment on \"On the Extraction of Purely Motor EEG Neural Correlates during an Upper Limb Visuomotor Task\"","date":"2022-07-22","arxiv_id":"2207.11168","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequence-models-for-drone-vs-bird","title":"Sequence Models for Drone vs Bird Classification","date":"2022-07-21","arxiv_id":"2207.10409","repositories_listed":0,"syntology":null},{"url":null,"slug":"correntropy-based-logistic-regression-with","title":"Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding","date":"2022-07-20","arxiv_id":"2207.09693","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-convolutional-neural-network-approach-to-2","title":"A Convolutional Neural Network Approach to Supernova Time-Series Classification","date":"2022-07-19","arxiv_id":"2207.09440","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-learning-for-the-resource","title":"Adaptive Learning for the Resource-Constrained Classification Problem","date":"2022-07-19","arxiv_id":"2207.09196","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-evidential-learning-for-few-shot","title":"Bayesian Evidential Learning for Few-Shot Classification","date":"2022-07-19","arxiv_id":"2207.13137","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-predictive-clustering-trees","title":"Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification","date":"2022-07-19","arxiv_id":"2207.09237","repositories_listed":0,"syntology":null},{"url":null,"slug":"consistent-polyhedral-surrogates-for-top-k","title":"Consistent Polyhedral Surrogates for Top-$k$ Classification and Variants","date":"2022-07-18","arxiv_id":"2207.08873","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-sequence-models-for-text-classification","title":"Deep Sequence Models for Text Classification Tasks","date":"2022-07-18","arxiv_id":"2207.08880","repositories_listed":0,"syntology":null},{"url":"/paper/multi-manifold-attention-for-vision","slug":"multi-manifold-attention-for-vision","title":"Multi-manifold Attention for Vision Transformers","date":"2022-07-18","arxiv_id":"2207.08569","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-fair-classification-with-mostly-private","title":"When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes","date":"2022-07-18","arxiv_id":"2207.08336","repositories_listed":0,"syntology":null},{"url":null,"slug":"mdm-visual-explanations-for-neural-networks","title":"MDM: Multiple Dynamic Masks for Visual Explanation of Neural Networks","date":"2022-07-17","arxiv_id":"2207.08046","repositories_listed":0,"syntology":null},{"url":"/paper/generative-adversarial-networks-based-on-1","slug":"generative-adversarial-networks-based-on-1","title":"Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification","date":"2022-07-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"forcing-the-whole-video-as-background-an","title":"Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization","date":"2022-07-14","arxiv_id":"2207.06659","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-discriminative-representation-via","title":"Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification","date":"2022-07-14","arxiv_id":"2207.06975","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-attention-mechanism-in-time-series","title":"Rethinking Attention Mechanism in Time Series Classification","date":"2022-07-14","arxiv_id":"2207.07564","repositories_listed":0,"syntology":null},{"url":null,"slug":"work-in-progress-safety-and-robustness","title":"Work In Progress: Safety and Robustness Verification of Autoencoder-Based Regression Models using the NNV Tool","date":"2022-07-14","arxiv_id":"2207.06759","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-classification-confidence-using","title":"Estimating Classification Confidence Using Kernel Densities","date":"2022-07-13","arxiv_id":"2207.06529","repositories_listed":0,"syntology":null},{"url":null,"slug":"journal-of-economic-literature-codes","title":"Journal of Economic Literature codes classification system (JEL)","date":"2022-07-13","arxiv_id":"2207.06076","repositories_listed":0,"syntology":null},{"url":null,"slug":"trusted-multi-scale-classification-framework","title":"Trusted Multi-Scale Classification Framework for Whole Slide Image","date":"2022-07-12","arxiv_id":"2207.05290","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dual-polarization-information-guided","title":"A Dual-Polarization Information Guided Network for SAR Ship Classification","date":"2022-07-11","arxiv_id":"2207.04639","repositories_listed":0,"syntology":null},{"url":null,"slug":"myers-briggs-personality-classification-from","title":"Myers-Briggs personality classification from social media text using pre-trained language models","date":"2022-07-10","arxiv_id":"2207.04476","repositories_listed":0,"syntology":null},{"url":null,"slug":"ngame-negative-mining-aware-mini-batching-for","title":"NGAME: Negative Mining-aware Mini-batching for Extreme Classification","date":"2022-07-10","arxiv_id":"2207.04452","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-improving-the-performance-of-glitch","title":"On Improving the Performance of Glitch Classification for Gravitational Wave Detection by using Generative Adversarial Networks","date":"2022-07-08","arxiv_id":"2207.04001","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-intrinsic-common-discriminative","title":"Towards Intrinsic Common Discriminative Features Learning for Face Forgery Detection using Adversarial Learning","date":"2022-07-08","arxiv_id":"2207.03776","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-embedding-dynamic-approach-to-self","title":"An Embedding-Dynamic Approach to Self-supervised Learning","date":"2022-07-07","arxiv_id":"2207.03552","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-e-commerce-product-classification","title":"Multimodal E-Commerce Product Classification Using Hierarchical Fusion","date":"2022-07-07","arxiv_id":"2207.03305","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-feature-extraction-for-memes","title":"Multimodal Feature Extraction for Memes Sentiment Classification","date":"2022-07-07","arxiv_id":"2207.03317","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hybrid-approach-for-binary-classification","title":"A Hybrid Approach for Binary Classification of Imbalanced Data","date":"2022-07-06","arxiv_id":"2207.02738","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-approach-for-classifying-1","title":"Deep Learning approach for Classifying Trusses and Runners of Strawberries","date":"2022-07-06","arxiv_id":"2207.02721","repositories_listed":0,"syntology":null},{"url":null,"slug":"humans-social-relationship-classification","title":"Humans Social Relationship Classification during Accompaniment","date":"2022-07-06","arxiv_id":"2207.02890","repositories_listed":0,"syntology":null}],"record_sha256":"001ef9cecd5ac9b3af681f08a4842dd677fc0b2b42f52d4711e7df291673d6d5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}