Yotaro Miyanishi
Papers
1
Total Citations
4
H-Index
1
About
Yotaro Miyanishi is a leading researcher in agricultural robotics and computer vision, with a focus on automating post-harvest processing. His work centers on developing intelligent robotic systems that can handle delicate, irregularly shaped produce, significantly advancing the field of precision agriculture. Miyanishi’s most notable contribution is his pioneering application of convolutional neural networks (CNNs) to solve the complex problem of fruit orientation detection. His highly cited 2022 paper, “Detection of Persimmon Posture by a Convolutional Neural Network for Fully Automating the Peeling Process,” demonstrates a breakthrough in enabling robots to autonomously pick and place randomly oriented persimmons for dried fruit production. This work directly addresses a critical bottleneck in the food industry, replacing manual labor with fast, robust machine vision. By integrating deep learning with robotic manipulation, Miyanishi has laid the groundwork for fully automated peeling lines, reducing waste and increasing efficiency. His research not only showcases the practical power of CNNs in real-world agricultural settings but also inspires future innovations in smart farming and food processing automation.
Research Focus
Key Achievements
Top Papers
- 1