Satoshi Moriya
Papers
1
Total Citations
4
H-Index
1
About
Satoshi Moriya is a researcher in computational neuroscience and computer vision, with a focus on biologically inspired models for motion perception. His work explores how neural networks can emulate the visual processing of biological systems, particularly in detecting local motion for stereo vision applications. Moriya’s most cited paper, "Complexity Reduction of Neural Network Model for Local Motion Detection in Motion Stereo Vision" (2017), introduces an efficient neural network architecture that reduces computational overhead while maintaining accuracy in motion detection tasks. This contribution is significant for advancing real-time vision systems in robotics and autonomous navigation. Although his citation count is modest, his research addresses a critical bottleneck in deploying bio-inspired models in resource-constrained environments. Moriya’s work bridges the gap between theoretical neuroscience and practical engineering, offering insights into how simplified neural circuits can achieve robust motion perception. His findings are particularly relevant for students and researchers interested in neuromorphic computing, visual processing, and the intersection of AI and biology.
Research Focus
Key Achievements
Top Papers
- 1