activity
20242026
collaborators

6 papers

cs.CV2026

Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation

Mingjie Li, Yizheng Chen, Md Tauhidul Islam +1

U-Net architectures have been instrumental in advancing biomedical image segmentation (BIS) but often struggle with capturing long-range information. One reason is the conventional…

cs.LG2026

Uncovering spatial tissue domains and cell types in spatial omics through cross-scale profiling of cellular and genomic interactions

Rui Yan, Xiaohan Xing, Xun Wang +3

Cellular identity and function are linked to both their intrinsic genomic makeup and extrinsic spatial context within the tissue microenvironment. Spatial transcriptomics (ST) offe…

cs.LG2025

Transformation of Biological Networks into Images via Semantic Cartography for Visual Interpretation and Scalable Deep Analysis

Sakib Mostafa, Lei Xing, Md. Tauhidul Islam

Complex biological networks are fundamental to biomedical science, capturing interactions among molecules, cells, genes, and tissues. Deciphering these networks is critical for und…

q-bio.NC2025

Revealing Neurocognitive and Behavioral Patterns by Unsupervised Manifold Learning from Dynamic Brain Data

Zixia Zhou, Junyan Liu, Wei Emma Wu +9

Dynamic brain data, teeming with biological and functional insights, are becoming increasingly accessible through advanced measurements, providing a gateway to understanding the in…

cs.LG2025

Deep-and-Wide Learning: Enhancing Data-Driven Inference via Synergistic Learning of Inter- and Intra-Data Representations

Md Tauhidul Islam, Lei Xing

Advancements in deep learning are revolutionizing science and engineering. The immense success of deep learning is largely due to its ability to extract essential high-dimensional…

cs.CV2024

Discovering distinctive elements of biomedical datasets for high-performance exploration

Md Tauhidul Islam, Lei Xing

The human brain represents an object by small elements and distinguishes two objects based on the difference in elements. Discovering the distinctive elements of high-dimensional d…