Application of Crop-Sum Algorithm to Character Recognition and Pedestrian Detection by Memory-Centric Computing

초록

In the era of artificial intelligence, the popularity of portable devices and the development of Computer Vision (CV) have improved the convenience of human productive life. However, with the substantial increase of application data and the problems of traditional Von Neumann Computing architectures in terms of performance bottlenecks and power consumption becoming more and more prominent, there is an urgent need to propose new computing models and related optimization algorithms. Memory-Centric Computing (MCC) is considered as a good hardware option to solve this problem. This paper also presents a Crop-Sum algorithm that can be widely used for computer vision development and analyzes its feasibility for use in applications such as character recognition and pedestrian detection. The work results show that the text recognition application optimized using this algorithm is significantly improved in terms of performance and power consumption, and that the Crop-Sum algorithm is feasible for implementing MCC and computational optimization. © 2023 IEEE.

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