Camille Simon Chane received her Msc in Electrical and Computer Engineering from the Georgia Institute of Technology in 2008. In 2009 she received the French Engineering diploma from ENSEA. She received her PhD in Imaging Instrumentation and Computer Vision from the University of Burgundy in 2013 for her work on the registration of featurless 3D and multispectral data.
In 2013 and 2014 she worked at the Cité de la musique, developing a luminescence multispectral camera for the study of violin varnishes. She was then part of Ryad Benosman’s Vision and Natural Computation team at the Institut de la Vision, where she acquired her expertise in event-based data processing. Since 2017 she is an Associate Professor at ENSEA, conducting her research in the Cell team of ETIS laboratory. Her interests continue to be related to data processing from unconventional sensor for public health and cultural heritage.
- Deeptera: Innovation for the surveillance of bloodsucking dipters
- Generation and characterisation of cerebral organoid images
- Event-based processing
- Evaluation of the condition of conservation of archival volumes
- AAEGAN Optimization by Purposeful Noise Injection for the Generation of Bright-Field Brain Organoid Images
- Deep-Learning Technology for Book Conservation Assessment in Libraries and Archives
- AAEGAN Loss Optimizations Supporting Data Augmentation on Cerebral Organoid Bright-Field Images
- Les outils de l'apprentissage profond au service de l'évaluation et de la conservation des archives