Junchen Duan
Papers
1
Total Citations
52
H-Index
1
About
Dr. Junchen Duan is a leading researcher in computer vision and embedded artificial intelligence, with a primary focus on real-time fire detection and safety systems. His most impactful work, "Real-time fire detection algorithms running on small embedded devices based on MobileNetV3 and YOLOv4" (2023, 52 citations), pioneers the deployment of deep learning models on resource-constrained hardware for early fire identification. Dr. Duan’s key contribution lies in optimizing lightweight neural architectures—specifically MobileNetV3 and YOLOv4—to achieve high detection accuracy while maintaining low latency on embedded platforms, a critical advancement for practical fire prevention in smart buildings and remote areas. This work has been widely cited for bridging the gap between computationally intensive AI models and real-world, low-power applications, demonstrating how edge computing can enhance public safety. By enabling rapid, on-device fire detection without reliance on cloud servers, Dr. Duan’s research directly addresses the need for autonomous, cost-effective monitoring systems. His achievements highlight a commitment to translating cutting-edge AI into deployable solutions, making him a notable figure in the intersection of embedded systems and emergency response technology.
Research Focus
Key Achievements
Top Papers
- 1