Area of research
Plant Science · Computer Vision and Pattern Recognition
Research interest
Research focused on PEST analysis and Crop, with related work in Convolutional neural network, Artificial intelligence, Occupancy. Notable publications include 'Crop pest image classification based on improved densely connected convolutional network', 'A Lightweight Crop Pest Classification Method Based on Improved MobileNet-V2 Model', and 'Novel occupancy detection method based on convolutional neural network model using PIR sensor and smart meter data'.
A Lightweight Crop Pest Classification Method Based on Improved MobileNet-V2 Model
Novel occupancy detection method based on convolutional neural network model using PIR sensor and smart meter data
Different life cycles of rice pests’ images recognition based on adaptive lightweight DC-ghost module
Crop pest image classification based on improved densely connected convolutional network
Combination of UAV and Raspberry Pi 4B: Airspace detection of red imported fire ant nests using an improved YOLOv4 model