Hardware based spatio-temporal neural processing backend for imaging sensors: towards a smart camera

Samiran Ganguly; Yunfei Gu; Mircea R. Stan; Avik W. Ghosh

doi:10.1117/12.2305137

14 May 2018 Hardware based spatio-temporal neural processing backend for imaging sensors: towards a smart camera

Samiran Ganguly, Yunfei Gu, Mircea R. Stan, Avik W. Ghosh

Proceedings Volume 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V; 106560Z (2018) https://doi.org/10.1117/12.2305137
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

In this work we show how we can build a technology platform for cognitive imaging sensors using recent advances in recurrent neural network architectures and training methods inspired from biology. We demonstrate learning and processing tasks specific to imaging sensors, including enhancement of sensitivity and signal-to-noise ratio (SNR) purely through neural filtering beyond the fundamental limits sensor materials, and inferencing and spatio-temporal pattern recognition capabilities of these networks with applications in object detection, motion tracking and prediction. We then show designs of unit hardware cells built using complementary metal-oxide semiconductor (CMOS) and emerging materials technologies for ultra-compact and energy-efficient embedded neural processors for smart cameras.

Conference Presentation

Citation Download Citation

Samiran Ganguly, Yunfei Gu, Mircea R. Stan, and Avik W. Ghosh "Hardware based spatio-temporal neural processing backend for imaging sensors: towards a smart camera", Proc. SPIE 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V, 106560Z (14 May 2018); https://doi.org/10.1117/12.2305137

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