A 915–1220 TOPS/W Hybrid In-Memory Computing based Image Restoration and Region Proposal Integrated Circuit for Neuromorphic Vision Sensors in 65nm CMOS

2022 IEEE Custom Integrated Circuits Conference (CICC)(2022)

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The bio-inspired asynchronous event-based neuromorphic vision sensors (NVS) are introducing a paradigm shift in visual information sensing and processing [1]. The feature of event-driven operation makes it ideal for low-power operation in the Internet-of-Things scenario such as traffic monitoring. However, the inherent noise in the sensor causes redundant wake-up operation and reduces tracking performance [2]. Energy efficient in-memory computing (IMC) based denoise operation allows blank-frame detection to gain 2X energy savings. Further energy savings can be obtained by exploiting spatial redundancy-objects usually occupy a small part ~5% of the frame in traffic monitoring [3]. Hence, region proposal (RP) is required to detect the region of interests (ROIs) in a valid frame along with their bounding box location coordinates, as shown in Fig. 1. For binary images, the conventional connected component labeling (CCL) algorithm [4] can propose ROIs by raster scanning the whole frame, but leads to longer search time and higher computing energy due to von Neumann operation. The promising IMC approach [3] has high energy efficiency, but has limited accuracy due to a simple algorithm constrained by in-memory operations as well as object fragmentation due to smooth surfaces (e.g. car windows) that do not generate events. In this work, we present a hybrid memory bit cell-collocated SRAM and DRAM (CRAM) consisting of 11 transistors for IMC-based image restoration (IR) and RP. The proposed CRAM supports image storage in SRAM and DRAM modes, denoise and region filling in diffusion mode and RP algorithm in projection mode.
binary images,conventional connected component labeling algorithm,ROIs,von Neumann operation,promising IMC approach,high energy efficiency,in-memory operations,IMC-based image restoration,image storage,region proposal integrated circuit,bio-inspired asynchronous event-based neuromorphic vision sensors,paradigm shift,visual information sensing,event-driven operation,low-power operation,Internet-of-Things scenario,traffic monitoring,redundant wake-up operation,energy efficient in-memory computing based denoise operation,blank-frame detection,energy savings,spatial redundancy-objects,bounding box location coordinates,size 65.0 nm
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