Dominique Ginhac

Laboratoire d’Électronique, Informatique et Image

Papers

2

Total Citations

17

H-Index

2

About

Dominique Ginhac is a leading researcher in real-time embedded vision systems, with a focus on high-performance edge computing and intelligent image processing. His work bridges the gap between advanced computer vision algorithms and practical hardware implementation, particularly for robotics and autonomous systems. A key contribution is the development of ACDnet, an innovative action detection network designed for real-time edge computing. This work, which has garnered 15 citations, introduces flow-guided feature approximation and memory aggregation techniques that enable efficient, low-latency video analysis directly on resource-constrained devices. Earlier, Ginhac pioneered a High Dynamic Range (HDR) real-time vision system for robotic applications, addressing the critical challenge of capturing clear visual information in scenes with extreme lighting contrasts. This foundational system demonstrated how HDR imaging could dramatically improve robot perception in unstructured environments. His research is characterized by a unique ability to translate complex theoretical concepts into deployable, hardware-optimized solutions, making him a notable figure in the field of embedded computer vision and edge AI.

Research Focus

Key Achievements

2
H-Index
2
Papers
17
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
ACDnet: An action detection network for real-time edge computing based on flow-guided feature approximation and memory aggregation
15 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Laboratoire d’Électronique, Informatique et Image

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago