Area of research
Plant Science · Analytical Chemistry
Research interest
Research interests include Computer science, Artificial intelligence, Pattern recognition (psychology), Mathematics, Linear discriminant analysis, and Segmentation.
Early Detection and Dynamic Grading of Sweet Potato Scab Based on Hyperspectral Imaging
SPVD-DETR: A novel real-time end-to-end object detector of sweetpotato virus disease from unmanned aerial vehicle ortho imagery
YOLOv7-GCA: A Lightweight and High-Performance Model for Pepper Disease Detection
Identification of sweetpotato virus disease-infected leaves from field images using deep learning
Attention-aided semantic segmentation network for weed identification in pineapple field
MT-Det: A novel fast object detector of maize tassel from high-resolution imagery using single level feature
Real-Time Lightweight Detection of Lychee Diseases with Enhanced YOLOv7 and Edge Computing
Feasibility of Detecting Sweet Potato (Ipomoea batatas) Virus Disease from High-Resolution Imagery in the Field Using a Deep Learning Framework
Lightweight Detection System with Global Attention Network (GloAN) for Rice Lodging
Attention-Aided Semantic Segmentation Network for Weed Identification in Pineapple Field
Real-Time Monitoring of Environmental Parameters in a Commercial Gestating Sow House Using a ZigBee-Based Wireless Sensor Network
Spectral Data Classification By One-Dimensional Convolutional Neural Networks
Identification of Cotton Growing Stage Based on Faster-RCNN
An Effective Prediction Approach for Moisture Content of Tea Leaves Based on Discrete Wavelet Transforms and Bootstrap Soft Shrinkage Algorithm
Detection of Spray-Dried Porcine Plasma (SDPP) based on Electronic Nose and Near-Infrared Spectroscopy Data
Cultivar Classification of Single Sweet Corn Seed Using Fourier Transform Near-Infrared Spectroscopy Combined with Discriminant Analysis
Single-Kernel FT-NIR Spectroscopy for Detecting Maturity of Cucumber Seeds Using a Multiclass Hierarchical Classification Strategy
Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis