Area of research
Media Technology · Atmospheric Science
Research interest
Research interests include Hyperspectral imaging, Computer science, Artificial intelligence, Pattern recognition (psychology), Remote sensing, and Multispectral image.
AIWSEN: Adaptive Information Weighting and Synchronized Enhancement Network for Hyperspectral Change Detection
A Cross-Scene Few-Shot Learning Based on Intra–Inter Domain Contrastive Alignment for Hyperspectral Image Change Detection
Semantic Tokenization-Based Mamba for Hyperspectral Image Classification
Progressive Hybrid-Order Hypergraph Framework for Hyperspectral Image Classification
Language-Guided and Similarity-Aware Network for Few-Shot Classification of Coastal Wetland Hyperspectral Images
DBCTNet: Double Branch Convolution-Transformer Network for Hyperspectral Image Classification
Adversarial Domain Adaptation Network With Calibrated Prototype and Dynamic Instance Convolution for Hyperspectral Image Classification
SAGN: Sharpening-Aware Graph Network for Hyperspectral Image Change Detection
DIEFEN: Differential Information-Enhanced Feature Exchange Network for Hyperspectral Change Detection
Generating high-resolution hyperspectral time series datasets based on unsupervised spatial-temporal-spectral fusion network incorporating a deep prior
Domain Invariant and Compact Prototype Contrast Adaptation for Hyperspectral Image Classification
FCFDA: Fine–Coarse–Fine Progressive Graph Framework With Distribution Alignment for Hyperspectral Image Change Detection
A robust and accurate feature matching method for multi-modal geographic images spatial registration
A Cross-Scene Self-Representative Network for Hyperspectral Band Selection
Domain Fusion Contrastive Learning for Cross-Scene Hyperspectral Image Classification
Coupled Temporal Variation Information Estimation and Resolution Enhancement for Remote Sensing Spatial–Temporal–Spectral Fusion
Cross-scene wetland mapping on hyperspectral remote sensing images using adversarial domain adaptation network
Refined Prototypical Contrastive Learning for Few-Shot Hyperspectral Image Classification
Deep Dynamic Adaptation Network Based on Joint Correlation Alignment for Cross-Scene Hyperspectral Image Classification
Deep Contrastive Learning Network for Small-Sample Hyperspectral Image Classification
Contrastive Learning Based on Category Matching for Domain Adaptation in Hyperspectral Image Classification
Self-Supervised Feature Learning Based on Spectral Masking for Hyperspectral Image Classification
Category-Specific Prototype Self-Refinement Contrastive Learning for Few-Shot Hyperspectral Image Classification
Two-Branch Deeper Graph Convolutional Network for Hyperspectral Image Classification
Semantic and spatial‐spectral feature fusion transformer network for the classification of hyperspectral image
Cross-Channel Dynamic Spatial–Spectral Fusion Transformer for Hyperspectral Image Classification
Unsupervised 3-D Tensor Subspace Decomposition Network for Spatial–Temporal–Spectral Fusion of Hyperspectral and Multispectral Images
Pyramidal Dilation Attention Convolutional Network With Active and Self-Paced Learning for Hyperspectral Image Classification
A Prototype and Active Learning Network for Small-Sample Hyperspectral Image Classification
Domain Adaptation in Remote Sensing Image Classification: A Survey