2 citations · 3 across the 5 of their papers we have counts for
5 papers
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering
Guangjie Zeng, Hao Peng, Angsheng Li +5
Hierarchical clustering is a fundamental machine-learning technique for grouping data points into dendrograms. However, existing hierarchical clustering methods encounter two prima…
Hierarchical Superpixel Segmentation via Structural Information Theory
Minhui Xie, Hao Peng, Pu Li +5
Superpixel segmentation is a foundation for many higher-level computer vision tasks, such as image segmentation, object recognition, and scene understanding. Existing graph-based s…
Multi-View Incongruity Learning for Multimodal Sarcasm Detection
Diandian Guo, Cong Cao, Fangfang Yuan +5
Multimodal sarcasm detection (MSD) is essential for various downstream tasks. Existing MSD methods tend to rely on spurious correlations. These methods often mistakenly prioritize…
Semi-Supervised Clustering via Structural Entropy with Different Constraints
Guangjie Zeng, Hao Peng, Angsheng Li +4
Semi-supervised clustering techniques have emerged as valuable tools for leveraging prior information in the form of constraints to improve the quality of clustering outcomes. Desp…
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs
Guangjie Zeng, Hao Peng, Angsheng Li +4
Skin lesion segmentation is a fundamental task in dermoscopic image analysis. The complex features of pixels in the lesion region impede the lesion segmentation accuracy, and exist…