⚡ 本页包含 AI 生成的分析内容，仅供参考
该论文提出了一款基于生物启发视觉感知算法的实时多目标识别处理器，实现了201.4GOPS的性能和496mW的低功耗。解决了以往处理器只能识别单个目标的问题，适用于视频监控、智能机器人等高级多目标识别应用。
recognition [1], was applied to the implementation of a high performance object recognition chip [2]. Even though the previous chip achieved 50% gain of computational cost [2], it could recognize only one object in a frame so that it is not suitable for advanced multi-object recognition applications such as video surveillance, intelligent robots, and autonomous vehicle navigation [3]. A real-time multi-object recognition processor is presented based on the bioinspired visual perception algorithm. The proposed recognition processor has 4 features: 1) 3-stage pipelining with grid-based region-of-interest (ROI) processing for high recognition rate, 2) Neural perception engine (NPE) with three bio-inspired neural and fuzzy processing units for multi-object perception and
Joo-Young Kim, Minsu Kim, Seungjin Lee, Jinwook Oh, Kwanho Kim,
Sejong Oh, Jeong-Ho Woo, Donghyun Kim, Hoi-Jun Yoo KAIST, Daejeon, Korea The visual attention mechanism, which is the way humans perform object