Area of research
Media Technology · Computer Vision and Pattern Recognition
Research interest
Research interests include Remote-Sensing Image Classification, Advanced Image Fusion Techniques, Remote Sensing and Land Use, and Image and Signal Denoising Methods.
Coupled Diffusion Posterior Sampling for Unsupervised Hyperspectral and Multispectral Images Fusion
Data-Driven Bidirectional Spatial-Adaptive Network for Weakly Supervised Object Detection in Remote Sensing Images
Cross-modal generative feature fusion based on label-consistency promoting VAE for transfer learning
SDG-DSB: Spectral Degradation Guided Diffusion Schrödinger Bridge for Hyperspectral Images Super-Resolution
Hyperspectral Anomaly Detection Based on Tensor Deep Subspace Prior Modeling
Distilling Object Detectors With Scale-Conscious Knowledge in Remote Sensing Images
Learning clique-based inter-class affinity for compositional zero-shot learning
SPDTT: Synergizing Prior-Spectrum-Guided Diffusion Model and Target-Aware Transformer for Hyperspectral Target Detection
See Hidden Insight From Transposition: Multiaxis Feature Aggregation for Aerial Object Detection
Image-Based Detection and Real-World Positioning: A Complete System for Anomaly Object Detection in High-Speed Railway Preventive Maintenance
HPGC-Diff: Hybrid-Prior Guided Coupled Diffusion for Unsupervised Hyperspectral Image Super-Resolution
ILRM: Imitation Learning-Based Resource Management for Integrated CPU–GPU Edge Systems With Renewable Energy Sources
Local–Global Information Perception Network for Salient Object Detection in Optical Remote Sensing Images
Swarm–Intelligence-Based Task Scheduling for Reliability Optimization of Integrated CPU–GPU Edge Platforms in Cyber–Physical–Social Systems
HMAFNet: Hybrid Mamba-Attention Fusion Network for Remote Sensing Image Semantic Segmentation
SOD-YOLOv8n: Small Object Detection in Remote Sensing Images Based on YOLOv8n
CAEM-DETR: Small Aerial Target Detection via Contrastive Attention-Enhanced Multidomain Fidelity Fusion
Efficient Low-Rank Representation for Hyperspectral Anomaly Detection via Pixel Segmentation
Spatial–Spectral Feature-Enhanced Mamba and SAM-Guided Hyperspectral Multiclass Change Detection
Bilinear Mixing Model-Based Spectral Decomposition Deep Neural Network for Hyperspectral Target Detection
Dual Prediction-Guided Distillation for Object Detection in Remote Sensing Images
Deformable Convolution-Enhanced Hierarchical Transformer with Spectral-Spatial Cluster Attention for Hyperspectral Image Classification.
Dual-Path Interactive U-Net for Unsupervised Hyperspectral Image Super-Resolution
More Accurate Constraints for Self-Supervised Learning in Remote Sensing Images-Based Object Detection
HSI Reconstruction: A Spectral Transformer With Tensor Decomposition and Dynamic Convolution
DPNet: A Lightweight Directional-Aware Pointwise Network for Dropper Defect Detection in High-Speed Railway Preventive Maintenance
Few-Shot Object Detection in Remote Sensing Images via Dynamic Adversarial Contrastive-Driven Semantic-Visual Fusion
A Biobjective Model-Driven Autocoder for Blind Hyperspectral Unmixing
Unsupervised Hyperspectral and Multispectral Image Blind Fusion Based on Deep Tucker Decomposition Network With Spatial-Spectral Manifold Learning.
Fast Processing of Massive Hyperspectral Image Anomaly Detection Based on Cloud-Edge Collaboration