Mian-Jhong Chiu
Papers
1
Total Citations
3
H-Index
1
About
Mian-Jhong Chiu is a researcher focused on efficient computer vision for autonomous systems, particularly in the areas of monocular depth estimation and lightweight neural network design. His most notable contribution is the development of a real-time monocular depth estimation method using an extremely light-weight neural network, which addresses the critical need for obstacle avoidance and environment sensing in autonomous driving and robotics. By leveraging only a single RGB camera—a low-cost, widely available sensor—his work enables accurate depth perception without the need for expensive LiDAR or stereo setups, making advanced perception more accessible. This research, published in 2021, has garnered 3 citations and represents a practical step toward deploying deep learning on resource-constrained platforms. Chiu’s focus on balancing computational efficiency with performance is particularly valuable for real-time applications, where speed and low power consumption are essential. His contributions help bridge the gap between cutting-edge computer vision research and real-world deployment in autonomous vehicles and mobile robots, offering a scalable solution for safer, more intelligent navigation.
Research Focus
Key Achievements
Top Papers
- 1