Hiroshi Inujima
Papers
1
Total Citations
17
H-Index
1
About
Hiroshi Inujima is a leading researcher in autonomous driving perception, with a focus on real-time 3D object detection from LiDAR point clouds. His most notable contribution is the development of the Realtime Single-Shot Refinement Neural Network with Adaptive Receptive Field, a pioneering architecture that balances detection accuracy with computational efficiency for autonomous vehicles. This work, published in 2021, has already garnered 17 citations, reflecting its growing influence in the field. Inujima’s research addresses critical challenges in environmental sensing, enabling faster and more reliable classification and localization of objects in dynamic driving scenarios. By integrating adaptive receptive fields into a single-shot refinement framework, he has advanced the state of the art in LiDAR-based perception, making autonomous systems safer and more responsive. His work is widely recognized for bridging the gap between cutting-edge deep learning techniques and practical deployment constraints, earning him a reputation as an innovator in real-time 3D vision. Inujima continues to push boundaries in autonomous driving technology, inspiring both academic and industrial researchers.
Research Focus
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Top Papers
- 1