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- W2502168579 abstract "Face detection is an important step in any face recognition systems, for the purpose of localizing and extracting face region from the rest of the images. The algorithms were built in C/C++ code and collaborated with OpenCV library. However, face detection system require high performance resources due to heavy real time measurement, in additional, it needs to be run on embedded platform. Therefore, platform system that host the face detection need to be tuned and enhanced to gain better performance from the standard settings and if possible, as good as desktop or laptop performance. In this paper, we propose two methods for enhancing the performance of the embedded platform. The two methods are OpenCV libraries multiprocessing and RAM tuning. The results shows that from one of the boards, Board 1 with quad core ARM Cortex-A7 processor capable to achieve almost as fast as laptop with Intel i3 processor. It can be concluded that embedded platform is capable to be a replacement for conventional computer system." @default.
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- W2502168579 date "2016-05-01" @default.
- W2502168579 modified "2023-09-25" @default.
- W2502168579 title "Embedded vision : Enhancing embedded platform for face detection system" @default.
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- W2502168579 doi "https://doi.org/10.1109/i2mtc.2016.7520358" @default.
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