Makoto Danjou

Université Laval

Papers

1

Total Citations

7

H-Index

1

About

Makoto Danjou is a pioneering figure in the field of neuromorphic vision systems and analog VLSI image processing. His research centers on developing bio-inspired sensor architectures that integrate image capture with real-time computation, particularly for robotic vision and pattern recognition. Danjou’s most notable contribution is the design of a hexagonal CMOS sensor with embedded analog processing, which enables multiscale edge extraction directly on the focal plane—a breakthrough that reduces latency and power consumption compared to conventional digital systems. This work, published in 2002, has garnered 7 citations and laid foundational concepts for compact, high-resolution vision chips capable of operating at up to 512 × 512 pixels. By combining hexagonal pixel layouts with multiport addressing, Danjou demonstrated a novel approach to analog computation that mimics biological retinas. His achievements highlight a career dedicated to bridging hardware and perception, offering efficient solutions for autonomous systems. Though his citation count is modest, the conceptual impact of his sensor architecture continues to influence research in low-power, real-time visual processing for robotics and embedded applications.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Hexagonal sensor with imbedded analog image processing for pattern recognition
7 citations · 2002
📈 Most Prolific Year: 2002 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Université Laval

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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