1 citations · 1 across the 4 of their papers we have counts for
4 papers
Structure-Aware Prototype Guided Trusted Multi-View Classification
Haojian Huang, Jiahao Shi, Zhe Liu +4
Trustworthy multi-view classification (TMVC) addresses the challenge of achieving reliable decision-making in complex scenarios where multi-source information is heterogeneous, inc…
Uncertainty-Guided Self-Questioning and Answering for Video-Language Alignment
Jin Chen, Kaijing Ma, Haojian Huang +4
The development of multi-modal models has been rapidly advancing, with some demonstrating remarkable capabilities. However, annotating video-text pairs remains expensive and insuff…
Trusted Unified Feature-Neighborhood Dynamics for Multi-View Classification
Haojian Huang, Chuanyu Qin, Zhe Liu +6
Multi-view classification (MVC) faces inherent challenges due to domain gaps and inconsistencies across different views, often resulting in uncertainties during the fusion process.…
Evidential Deep Partial Multi-View Classification With Discount Fusion
Haojian Huang, Zhe Liu, Sukumar Letchmunan +3
Incomplete multi-view data classification poses significant challenges due to the common issue of missing views in real-world scenarios. Despite advancements, existing methods ofte…