activity
20222026
most citedHSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classification

3 citations · 7 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026★ 1 cited

Implicit spatial-frequency fusion of hyperspectral and lidar data via kolmogorov-arnold networks

Zekun Long, Judy X. Yang, Jing Wang +3

Hyperspectral image (HSI) classification is challenging in complex scenes due to spectral ambiguity, spatial heterogeneity, and the strong coupling between material properties and…

cs.LG2025

Phase-Locked SNR Band Selection for Weak Mineral Signal Detection in Hyperspectral Imagery

Judy X Yang

Hyperspectral imaging offers detailed spectral information for mineral mapping; however, weak mineral signatures are often masked by noisy and redundant bands, limiting detection p…

cs.CV2025

HSLiNets: Evaluating Band Ordering Strategies in Hyperspectral and LiDAR Fusion

Judy X Yang, Jing Wang, Zhuanfeng +3

The integration of hyperspectral imaging (HSI) and Light Detection and Ranging (LiDAR) data provides complementary spectral and spatial information for remote sensing applications.…

cs.CV2024

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks

Judy X Yang, Jing Wang, Chen Hong Sui +2

The integration of hyperspectral imaging (HSI) and LiDAR data within new linear feature spaces offers a promising solution to the challenges posed by the high-dimensionality and re…

cs.CV2024

Hyperspectral Images Efficient Spatial and Spectral non-Linear Model with Bidirectional Feature Learning

Judy X Yang, Jing Wang, Zekun Long +2

Classifying hyperspectral images (HSIs) is a complex task in remote sensing due to the high-dimensional nature and volume of data involved. To address these challenges, we propose…

eess.IV2024★ 1 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.CV2024★ 2 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.CV2024★ 3 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…

cs.CR2022

A hybrid privacy protection scheme for medical data

Judy X Yang, Hui Tian, Alan Wee-Chung Liew +1

Healthcare data contains sensitive information, and it is challenging to persuade healthcare data owners to share their information for research purposes without any privacy assura…