Area of research
Artificial Intelligence · Computer Vision and Pattern Recognition
Research interest
Research interests include Computer science, Artificial intelligence, Cluster analysis, Discriminative model, Anomaly detection, and Multi-label classification.
Attention-Induced Embedding Imputation for Incomplete Multi-View Partial Multi-Label Classification
Deep dual incomplete multi-view multi-label classification via label semantic-guided contrastive learning
Differentiated knowledge distillation: Patient-specific single-sample personalization for electrocardiogram diagnostic models
Information Recovery-Driven Deep Incomplete Multiview Clustering Network
DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification
Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-view Clustering
Weakly Supervised Video Anomaly Detection via Self-Guided Temporal Discriminative Transformer
Pixel-Level Anomaly Detection via Uncertainty-aware Prototypical Transformer