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Multi-Label Classification

multilabel graph classification with highest result

Papers

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Showing 51–75 of 1198 papers

TitleStatusHype
Causality Compensated Attention for Contextual Biased Visual RecognitionCode1
Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray ImagesCode1
Category-Wise Fine-Tuning for Image Multi-label Classification with Partial LabelsCode1
FedMLP: Federated Multi-Label Medical Image Classification under Task HeterogeneityCode1
Amalgamating Knowledge From Heterogeneous Graph Neural NetworksCode1
A data-centric approach for assessing progress of Graph Neural NetworksCode1
VALUED -- Vision and Logical Understanding Evaluation DatasetCode1
CheXclusion: Fairness gaps in deep chest X-ray classifiersCode1
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image ClassificationCode1
GlideNet: Global, Local and Intrinsic based Dense Embedding NETwork for Multi-category Attributes PredictionCode1
Class-Incremental Lifelong Learning in Multi-Label ClassificationCode1
Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image RecognitionCode1
Densely Connected Convolutional NetworksCode1
DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label ClassificationCode1
Deep Smart Contract Intent DetectionCode1
Asymmetric Loss For Multi-Label ClassificationCode1
Dense-Caption Matching and Frame-Selection Gating for Temporal Localization in VideoQACode1
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
ContractNLI: A Dataset for Document-level Natural Language Inference for ContractsCode1
Contextual Debiasing for Visual Recognition With Causal MechanismsCode1
Cross- and Intra-image Prototypical Learning for Multi-label Disease Diagnosis and InterpretationCode1
DECAF: Deep Extreme Classification with Label FeaturesCode1
Asymmetric Polynomial Loss For Multi-Label ClassificationCode1
Deep Label Distribution Learning with Label AmbiguityCode1
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
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All datasetsCheXpertMS-COCOPASCAL VOC 2007NUS-WIDEChestX-ray14OpenImages-v6PASCAL VOC 2012MLRSNetMRNetMIMIC-CXR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CFT (ensemble) Macao Polytechnic UniversityAVERAGE AUC ON 14 LABEL0.93—Unverified
2Hierarchical-Learning-V1 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
3DeepAUC-v1AVERAGE AUC ON 14 LABEL0.93—Unverified
4Conditional-Training-LSRAVERAGE AUC ON 14 LABEL0.93—Unverified
5Hierarchical-Learning-V4 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
6YWW(ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
7Hierarchical-Learning-V0 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
8Conditional-Training-LSR-V1AVERAGE AUC ON 14 LABEL0.93—Unverified
9DeepCNNsGM(ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
10Multi-Stage-Learning-CNN-V3 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified