Yuichiro Shibata

About

Yuichiro Shibata is a researcher whose work spans surgical robotics, autonomous driving, and personal robotics, with a focus on real-time image processing and hardware implementation. His most cited paper (2019, 5 citations) introduces a CNN architecture for surgical image segmentation, featuring a recursive network structure to mitigate overfitting—a critical step toward automating laparoscope control in minimally invasive surgery, reducing the need for a human camera assistant. In 2022 (4 citations), Shibata advanced autonomous driving technology by implementing contour detection based on the Helmholtz principle on an FPGA, enabling efficient, low-cost white-line detection for driver assistance systems. Earlier, in 1997 (2 citations), he developed a reconfigurable sensor-data processing system for personal robots, showcasing his long-standing interest in adaptable hardware solutions. Shibata’s contributions lie at the intersection of computer vision, embedded systems, and robotics, demonstrating a consistent drive to make intelligent systems more autonomous and practical through efficient hardware-software co-design. His work holds promise for safer surgeries, smarter vehicles, and more capable personal robots.

Research Focus

Key Achievements

Top Papers

1. 1
   CNN Architecture for Surgical Image Segmentation Systems with Recursive Network Structure to Mitigate Overfitting

   5 citations · 2019
2. 2
   FPGA implementation of contour detection based on Helmholtz principle

   4 citations · 2022
3. 3
   A reconfigurable sensor-data processing system for personal robots

   2 citations · 1997

Key Collaborators

Contact & Links