Area of research
Computer Vision and Pattern Recognition · Plant Science
Research interest
Research interests include Computer science, Artificial intelligence, Computer vision, Change detection, Joint (building), and Image (mathematics).
FDRW-Net: A feature dynamic reweighting network for cotton disease detection in natural scenes
YOLOv8-LSI: Enhanced Weed Detection in Agricultural Fields Using Large Convolutional Kernels and Dimensionality-Expanded Channel Attention
A Depth Semantic Perception Network for Camouflage Object Detection
A lightweight weed detection model with global contextual joint features
Depth prior-based stable tensor decomposition for video snow removal
Joint Colour Casts Correction and Zero-Shot Learning for Real-World Sand-Dust Image Enhancement
Video image change detection under a wide field of view in foggy weather
X-ray Image Enhancement Based on Adaptive Gradient Domain Guided Image Filtering
A fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and interframe detection strategy
A method to improve the accuracy of SAR image change detection by using an image enhancement method