Area of research
Plant Science · Computer Vision and Pattern Recognition
Research interest
Research focused on Artificial intelligence and Support vector machine, with related work in Computer vision, Random forest, Ripeness. Notable publications include 'Rachis detection and three-dimensional localization of cut off point for vision-based banana robot', 'Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model', and 'An Accurate Forest Fire Recognition Method Based on Improved BPNN and IoT'.
Pose estimation for long-staple cotton picking based on growth-relationship keypoint constraints and vision–language model reasoning
Trajectory Tracking Control of a Six-Axis Robotic Manipulator Based on an Extended Kalman Filter-Based State Observer
Vision-Based Perception and Execution Decision-Making for Fruit Picking Robots Using Generative AI Models
CTDA: an accurate and efficient cherry tomato detection algorithm in complex environments
Prediction of Mild Moldy‐Core Disease in Apples Based on Fusion Features of Near‐Infrared Transmission Spectroscopy and Acoustic Vibration Signals
A bionic vision method for extracting motion information of small-target in cotton field backgrounds
A method for nighttime tomato fruit detection and occlusion judgment based on deep learning and image processing
Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model
Efficient three-dimensional reconstruction and skeleton extraction for intelligent pruning of fruit trees
An Accurate Forest Fire Recognition Method Based on Improved BPNN and IoT
Rachis detection and three-dimensional localization of cut off point for vision-based banana robot
Forest fire monitoring via uncrewed aerial vehicle image processing based on a modified machine learning algorithm
Grand Challenges of Machine-Vision Technology in Civil Structural Health Monitoring