Dr. Hongkai Yu, an associate professor in the Department of Electrical and Computer Engineering (ECE) will join researchers from the University of Kentucky to apply computer vision and artificial intelligence to the task of improving crop quality and yields in large scale greenhouses. The work is funded by a nearly $1.2 million grant from the National Science Foundation, titled “An Autonomous Robotic System for Precision and High-Throughput Tomato Phenotyping in Large-Scale Greenhouses.” 

Dr. Yu and his students will design computer vision and AI algorithms that use camera imaging of the plants for phenotyping. Phenotypes (visible/observable traits) like fruit size/weight, number of fruit, and plant architecture can be used to optimize yield. The computer vision/AI system will improve the speed and quality of plant data collection and analysis while also reducing potential work hazards for greenhouse workers.

Dr. Yu directs the Cleveland Vision & AI Lab, which pursues innovative research in the areas of computer vision, machine learning, deep learning and artificial intelligence. His lab recently published CSU’s first paper in the high impact journal Computer Vision and Pattern Recognition (CVPR). CSU PhD students Jinlong Li (below left) and Xinyu Liu (below right) presented the paper at the 2024 CVPR conference.

Jinlong Li, Baolu Li, Zhengzhong Tu, Xinyu Liu, Qing Guo, Felix Juefei-Xu, Runsheng Xu, Hongkai Yu. Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.