Masahiro Shigeta
Papers
1
Total Citations
17
H-Index
1
About
Masahiro Shigeta is a leading researcher in precision livestock farming, with a primary focus on the application of computer vision and deep learning to dairy cattle management. His work centers on developing non-invasive, automated monitoring systems to improve animal welfare and farm efficiency. Shigeta’s most notable contribution is his pioneering 2018 study on the automatic measurement and determination of body condition score (BCS) in cows using 3D images and convolutional neural networks (CNNs). This work, which has garnered 17 citations, directly addresses a critical challenge in modern Japanese agriculture: as the number of rearing houses declines but herd sizes increase, farmers require scalable, objective tools for individual animal health assessment. By replacing subjective manual scoring with a reliable, camera-based system, Shigeta’s research enables real-time, data-driven herd management. His innovative approach not only enhances the accuracy of BCS evaluation but also reduces labor demands, making it a vital contribution to sustainable livestock practices. Shigeta’s work stands out for its practical impact, bridging cutting-edge AI technology with the urgent needs of the agricultural sector.
Research Focus
Key Achievements
Top Papers
- 1