A Hybrid Deep Learning Method of Fast Object Detection for Embedded System
| Autor: | Chen, Guan-Ren, 陳冠任 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 Nowadays, there are a plenty of the computer vision applications on embedded system. However, it is not good to run computer vision applications on embedded systems which will take much computation and power consumption. This study aims to measure the power consumption, the accuracy and the performance of different algorithm running on different platform to give the suggestion of choosing algorithm on the platform so to meet the request of the performance and power consumption for different applications in different situation. In this thesis, we build a 3D plot which composed by power, accuracy and FPS. Further, from microscopic point of view, we choose one higher accuracy but slower detection algorithm and one lower accuracy but faster detection algorithm. Since video has the characteristics that the frame in video will be similar to its next frame, we run these two detection algorithm on the video frames alternatively and use the result produced by higher accuracy algorithm to correct the result produced by lower accuracy algorithm so that we can achieve the result that the accuracy is close to the higher accuracy algorithm but its execution time significantly shortened. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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