Christopher Soell

Fraunhofer Institute for Integrated Circuits

Papers

Total Citations

H-Index

About

Christopher Soell is a researcher whose work sits at the intersection of analog circuit design and smart vision systems, with a particular focus on low-power, edge-computing image sensors. His most-cited paper, "Low-power analog smart camera sensor for edge detection" (2016, 12 citations), introduces an intelligent analog image sensor system tailored for applications requiring efficient edge or marker detection. This system integrates a 3×3 read-out CMOS image sensor with an analog Sobel filter stage, along with operational amplifiers and comparators, to compute a 1-bit edge map directly on the sensor—eliminating the need for power-hungry digital processing. Soell’s contribution is significant for enabling real-time, low-power computer vision in resource-constrained environments, such as embedded or IoT devices. By moving computation into the analog domain, his work demonstrates a path toward smarter, more energy-efficient cameras. Though his citation count is still growing, this foundational paper has established him as a contributor to the field of analog in-memory and near-sensor processing, with implications for autonomous systems and smart surveillance.