My career objective is to become a leading researcher and practitioner in the field of
CS, with a focus on applying machine learning and neural network models to solve
complex, real-world challenges. My journey in CS has been marked by a series of
research accomplishments and hands-on experiences that have honed my skills in
neural networks, image recognition, and optimization algorithms. Each experience
has deepened my commitment to advancing knowledge in this field and contributing
to innovations that can transform various industries.
Recently, I was fortunate enough to join Professor Li Liujun's research team at the
University of Idaho and undertake model code optimization work at the 4th Dutch
Greenhouse Planting Competition. Through unremitting efforts, I have successfully
improved the recognition accuracy of the model and achieved significant results. At
present, under the careful guidance of Professor Li, I am fully committed to the
research in the field of edge comp
Identiffcation of rice disease under complex background based on PSOC-DRCNet
Team Leader, Supervisor: Prof. Guoxiong Zhou May 2023 - January 2024
PMANet: a time series forecasting model for Chinese stock price prediction
Core Member, Supervisor: Prof. Guoxiong Zhou August 2023- May 2024
The fourth session of the Dutch Greenhouse Planting Competition
Member, Supervisor: Prof. Liujun Li December 2023 - August 2024
AISOA-SSormer: An Effective Image Segmentation Method for Rice Leaf Disease Based on the Transformer Architecture
Core Member, Supervisor: Prof. Guoxiong Zhou December 2023 - August 2024
A DualModeAttention (DMA) method is proposed, which adaptive captures the featured salient regions of rice disease images in diversity of r
We introduce MTFC to improve the network’s capability in processing complex features of long sequences. This approach involves taking input