A 201.4GOPS 496mW real-time multi-object recognition processor with bio-inspired neural perception engine

@article{Kim2009A24,
  title={A 201.4GOPS 496mW real-time multi-object recognition processor with bio-inspired neural perception engine},
  author={Joo-Young Kim and Minsu Kim and Seungjin Lee and Jinwook Oh and Kwanho Kim and Sejong Oh and Jeong-Ho Woo and Donghyun Kim and Hoi-Jun Yoo},
  journal={2009 IEEE International Solid-State Circuits Conference - Digest of Technical Papers},
  year={2009},
  pages={150-151,151a}
}
The visual attention mechanism, which is the way humans perform object 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]. 
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