collaborators

16 papers

cs.LG2026

Evaluating Machine Learning Models for Post-Wildfire Debris-Flow Prediction

Quinn Ledingham, Zhengsen Xu, Yimin Zhu +6

Prediction of post-wildfire debris flows is critical for mitigating hazards to communities, infrastructure, and resources during intense rainfall in recently burned areas. However,…

cs.CV2026

A Novel Graph-Regulated Disentangling Mamba Model with Sparse Tokens for Enhanced Tree Species Classification from MODIS Time Series

Motasem Alkayid, Zhengsen Xu, Saeid Taleghanidoozdoozan +7

Although tree species classification from Moderate Resolution Imaging Spectroradiometer (MODIS) time series data is critical for supporting various environmental applications, it i…

cs.CV2026

Defending against Patch-Based and Texture-Based Adversarial Attacks with Spectral Decomposition

Wei Zhang, Xinyu Chang, Xiao Li +2

Adversarial examples present significant challenges to the security of Deep Neural Network (DNN) applications. Specifically, there are patch-based and texture-based attacks that ar…

cs.CV2026

Unmixing-Guided Spatial-Spectral Mamba with Clustering Tokens for Hyperspectral Image Classification

Yimin Zhu, Lincoln Linlin Xu

Although hyperspectral image (HSI) classification is critical for supporting various environmental applications, it is a challenging task due to the spectral-mixture effect, the sp…

cs.CV2026

DSCSNet: A Dynamic Sparse Compression Sensing Network for Closely-Spaced Infrared Small Target Unmixing

Zhiyang Tang, Yiming Zhu, Ruimin Huang +4

Due to the limitations of optical lens focal length and detector resolution, distant clustered infrared small targets often appear as mixed spots. The Close Small Object Unmixing (…

cs.CV2026

mHC-HSI: Clustering-Guided Hyper-Connection Mamba for Hyperspectral Image Classification

Yimin Zhu, Zack Dewis, Quinn Ledingham +6

Recently, DeepSeek has invented the manifold-constrained hyper-connection (mHC) approach which has demonstrated significant improvements over the traditional residual connection in…