Shida Zhao

Jiangsu Academy of Agricultural Sciences, Huazhong Agricultural University

Papers

Total Citations

H-Index

About

Shida Zhao is a researcher at the forefront of intelligent agricultural automation, specializing in computer vision and deep learning for livestock management and meat processing. Her work focuses on developing non-invasive, real-time monitoring systems that enhance animal welfare and operational efficiency in modern farming. Zhao’s key contributions include pioneering an automated body weight estimation method for captive rabbits using an improved Mask RCNN, which reduces the need for stressful manual handling. This work has garnered 9 citations, reflecting its practical significance. She also advanced the field of meat quality control by proposing a real-time classification and detection system for mutton parts based on a Single Shot Multi-Box Detector (SSD), achieving 6 citations for its application in slaughterhouse environments. Additionally, Zhao developed a fully convolutional neural network for precise segmentation of sheep rib regions, a critical step toward intelligent robotic sorting on conveyor belts. Her research directly addresses the challenges of precision livestock farming, offering scalable solutions that minimize human intervention while improving accuracy. Zhao’s work is notable for its direct industrial applicability, bridging the gap between cutting-edge AI and practical agricultural needs.