Papers
6
Total Citations
38
H-Index
4
About
Marc Reichenbach is a leading researcher at the intersection of embedded computer vision, smart camera systems, and hardware security for the Internet of Things. His work focuses on designing intelligent, low-power image processing architectures that push computation directly onto the sensor. A key contribution is the development of an analog smart camera sensor for edge detection, which integrates a CMOS image sensor with an analog Sobel stage to achieve real-time, low-power visual processing—a foundational paper with 12 citations. He also pioneered the concept of distributed vision with smart pixels, exploring how sensor fields can compute higher-level properties without centralized control, earning 10 citations. More recently, Reichenbach has applied deep neural networks on FPGAs for detecting improvised landmines from GPR imagery (7 citations), demonstrating a commitment to socially impactful technology. His FAUPU design framework (4 citations) provides a systematic approach for building programmable image processing architectures, while his latest work on trusted computing architectures for IoT devices (2024) addresses critical security challenges. Reichenbach’s research bridges analog and digital, hardware and algorithms, making him a key figure in advancing efficient, secure, and intelligent embedded vision systems.
Research Focus
Key Achievements
Top Papers
- 1Low-power analog smart camera sensor for edge detection12 citations · 2016
- 2Distributed vision with smart pixels10 citations · 2009
- 3
- 4
- 5Trusted Computing Architectures for IoT Devices3 citations · 2024
- 6InjectMeAI—Software Module of an Autonomous Injection Humanoid2 citations · 2022