Area of research
Molecular Biology · Statistical and Nonlinear Physics
Research interest
Research interests include Computer science, Spike (software development), Artificial intelligence, Pattern recognition (psychology), Object detection, and Deep learning.
Riboformer: a deep learning framework for predicting context-dependent translation dynamics
Small and Oriented Wheat Spike Detection at the Filling and Maturity Stages Based on WheatNet
Improving multi-scale detection layers in the deep learning network for wheat spike detection based on interpretive analysis
A deep learning method for oriented and small wheat spike detection (OSWSDet) in UAV images
A Wheat Spike Detection Method in UAV Images Based on Improved YOLOv5
Chemical perturbations reveal that RUVBL2 regulates the circadian phase in mammals