1 citations · 1 across the 6 of their papers we have counts for
6 papers
Broad stochastic configuration residual learning system for norm-convergent universal approximation
Han Su, Zhongyan Li, Wanquan Liu
Universal approximation serves as the foundation of neural network learning algorithms. However, some networks establish their universal approximation property by demonstrating tha…
AFR-CLIP: Enhancing Zero-Shot Industrial Anomaly Detection with Stateless-to-Stateful Anomaly Feature Rectification
Jingyi Yuan, Chenqiang Gao, Pengyu Jie +3
Recently, zero-shot anomaly detection (ZSAD) has emerged as a pivotal paradigm for industrial inspection and medical diagnostics, detecting defects in novel objects without requiri…
MATCNN: Infrared and Visible Image Fusion Method Based on Multi-scale CNN with Attention Transformer
Jingjing Liu, Li Zhang, Xiaoyang Zeng +2
While attention-based approaches have shown considerable progress in enhancing image fusion and addressing the challenges posed by long-range feature dependencies, their efficacy i…
Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars
Xuan Huang, Hanhui Li, Wanquan Liu +4
In this paper, we propose to create animatable avatars for interacting hands with 3D Gaussian Splatting (GS) and single-image inputs. Existing GS-based methods designed for single…
A Point-Neighborhood Learning Framework for Nasal Endoscope Image Segmentation
Pengyu Jie, Wanquan Liu, Chenqiang Gao +6
Lesion segmentation on nasal endoscopic images is challenging due to its complex lesion features. Fully-supervised deep learning methods achieve promising performance with pixel-le…
A Novel Exploration of Diffusion Process based on Multi-types Galton-Watson Forests
Yanjiao Zhu, Qilin Li, Wanquan Liu +2
Diffusion is a commonly used technique for spreading information from point to point on a graph. The rationale behind diffusion is not clear. And the multi-types Galton-Watson fore…