Mr. Xiangxue Chen | Computer Vision Award | Best Researcher Award

Mr. Xiangxue Chen | Computer Vision Award | Jinan University | China

Mr. Xiangxue Chen is a motivated and academically accomplished postgraduate student currently pursuing a Master’s degree in Agricultural Engineering and Information Technology at Gansu Agricultural University, College of Information Science and Technology, building on previous undergraduate training in Network Engineering at Jinan University Quancheng College. With strong enthusiasm for the integration of artificial intelligence into modern agriculture, the research interests of Xiangxue Chen focus on Deep Learning, Smart Agriculture, and Agricultural Informatization, particularly on intelligent livestock measurement and management. During the Master’s program, Xiangxue Chen led impactful research on automatic cattle body size measurement based on deep learning, contributing to livestock breeding efficiency and smart farming systems. The technical approach included designing lightweight keypoint detection models using frameworks like YOLOv8-pose, automatically identifying cattle and predicting anatomical keypoints, followed by measurement transformation through Euclidean estimation and relevant calibration parameters to provide real-world body dimension results. A dedicated dataset was independently developed by visiting and acquiring cattle images at the National Jinnan Cattle Genetic Resource Gene Conservation Center in Yuncheng, Shanxi Province, demonstrating initiative in data collection and preprocessing. Xiangxue Chen has authored multiple impactful academic publications, including one SCI paper in the journal Symmetry as first author and two additional first- and co-authored papers in Peking University Core & CSCD-C journals such as the Journal of Nanjing Agricultural University and Journal of South China Agricultural University, as well as a first-author software copyright titled Automatic Cattle Body Measurement System Based on Improved YOLOv8-pose. Throughout graduate studies, excellence has been recognized by receiving the Postgraduate Academic Scholarship twice (October 2023 and October 2024). In terms of professional skills, Xiangxue Chen is proficient in PyTorch for deep-learning tasks including detection, segmentation, pose estimation, and classification, while also being skilled in Python, C#, Java, HTML, and research tools such as Origin, Visio, MathType, and Zotero. Additionally, Xiangxue Chen holds certifications in Web Front-End Development (Primary Level) and as an Artificial Intelligence Trainer (Advanced Level). Overall, Xiangxue Chen stands out as a talented young researcher dedicated to advancing agricultural digitalization and intelligent livestock system innovation, contributing meaningful scholarly achievements with great potential for future development in smart agriculture technology.