SpikeSen: Low-Latency In-Sensor-Intelligence Design With Neuromorphic Spiking Neurons

IEEE Transactions on Circuits and Systems II: Express Briefs(2023)

引用 0|浏览50
暂无评分
摘要
In-sensor-processing (ISP) paradigm has been exploited in state-of-the-art vision system designs to pave the way towards power-efficient sensing and processing. The redundant data transmission between sensors and processors is significantly minimized by local computation within each pixel. However, existing ISP designs suffer from limited frame rates and degraded fill factors. In this brief, we introduce a low-latency in-sensor-intelligence neuromorphic vision system using neuromorphic spiking neurons, namely SpikeSen. SpikeSen directly operates on the photocurrents and executes the computation in the frequency domain, reducing the long exposure time and speeding up the computation. Experiments show that SpikeSen can achieve more than 6.1x computation speedup compared to existing ISP designs with competitive energy consumption per pixel.
更多
查看译文
关键词
Neurons,Photoconductivity,Program processors,Image sensors,Sensors,Machine vision,Low latency communication,In-sensor-processing,neuromorphic computing,low latency,frequency-domain computation,CMOS
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要