2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CV2026
Learning Task-Aware Sampling with Shared Saliency through Density-Equalizing Mappings
Tsz Lok Ip, Han Zhang, Lok Ming Lui
In image and surface-based learning tasks, convolutional features are typically extracted using receptive fields that are sampled uniformly across the entire domain. However, infor…
cs.CV2025
Quasi-Conformal Convolution : A Learnable Convolution for Deep Learning on Simply Connected Open Surfaces
Han Zhang, Tsz Lok Ip, Lok Ming Lui
Deep learning on non-Euclidean domains is important for analyzing complex geometric data that lacks common coordinate systems and familiar Euclidean properties. A central challenge…
eess.IV2022★ 2 cited
Topology-Preserving Segmentation Network: A Deep Learning Segmentation Framework for Connected Component
Han Zhang, Lok Ming Lui
Medical image segmentation, which aims to automatically extract anatomical or pathological structures, plays a key role in computer-aided diagnosis and disease analysis. Despite th…