most citedPrivacy-Preserving in Medical Image Analysis: A Review of Methods and Applications

3 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Neuroscience-inspired Staged Representation Learning with Disentangled Coarse- and Fine-Grained Semantics for EEG Visual Decoding

Xiang Gao, Hui Tian, Yanming Zhu +2

Decoding visual information from electroencephalography (EEG) signals remains a fundamental challenge in brain-computer interfaces and medical rehabilitation. Existing EEG visual d…

cs.CV20243 cited

Privacy-Preserving in Medical Image Analysis: A Review of Methods and Applications

Yanming Zhu, Xuefei Yin, Alan Wee-Chung Liew +1

With the rapid advancement of artificial intelligence and deep learning, medical image analysis has become a critical tool in modern healthcare, significantly improving diagnostic…

eess.IV20241 cited

LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image Classification

Judy X Yang, Jun Zhou, Jing Wang +2

The fusion of hyperspectral and LiDAR data has been an active research topic. Existing fusion methods have ignored the high-dimensionality and redundancy challenges in hyperspectra…

cs.CV20242 cited

Unsupervised Band Selection Using Fused HSI and LiDAR Attention Integrating With Autoencoder

Judy X Yang, Jun Zhou, Jing Wang +2

Band selection in hyperspectral imaging (HSI) is critical for optimising data processing and enhancing analytical accuracy. Traditional approaches have predominantly concentrated o…

cs.CV20243 cited

HSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classification

Judy X Yang, Jun Zhou, Jing Wang +2

Classifying hyperspectral images is a difficult task in remote sensing, due to their complex high-dimensional data. To address this challenge, we propose HSIMamba, a novel framewor…