A 915-1220 TOPSW 976-1301 GOPS Hybrid In-Memory Computing Based Always-On Image

Abstract

Neuromorphic vision sensors (NVSs) save energy and reduce data at the source by asynchronously recording changes in temporal contrast. Thus, NVS provides an opportunity to exploit temporal and spatial redundancy in video streams by enabling the following deep neural network (DNN) processor for object recognition to process only foreground object regions in valid frames. However, the NVS data inevitably contains noise leading to false frame generation. Moreover, objects may be fragmented due to a