⚡ 本页包含 AI 生成的分析内容，仅供参考
该论文设计了一款面向HD 720p视频流的实时运动目标识别处理器，功耗仅320mW，性能达342GOPS，解决了无人机和移动增强现实等应用中因低灵敏度CMOS传感器导致的运动/相机模糊噪声下的鲁棒识别问题。
unmanned aerial vehicles (UAVs) and mobile augmented reality that require robust and fast recognition in the presence of dynamic camera noise. Devices in such applications suffer from severe motion/camera blur noise in low-light conditions due to low-sensitivity CMOS image sensors, and therefore require higher computing power to obtain robust results vs. devices used in still image applications. Moreover, HD resolution has become so universal today that even smartphones support applications with HD resolution. However, many object recognition processors [1][2] and accelerators [3] reported for mobile applications only support SD resolution due to the computational complexity of object recognition algorithms. For example, the prior works [1] and [2] obtain 11f/s and 7f/s processing speed for HD video streams, respectively, which is far below
Jinwook Oh, Gyeonghoon Kim, Junyoung Park, Injoon Hong,
Seungjin Lee, Hoi-Jun Yoo KAIST, Daejeon, Korea Moving object recognition in a video stream is crucial for applications such as