嵌入式电动汽车边缘计算检测的设计与实现

2021 4th International Conference on Artificial Intelligence for Industries (AI4I) Pub Date : 2021-09-01 DOI:10.1109/AI4I51902.2021.00027

Ching-Lung Su, W. Lai, Jun-Yun Wu, Pin-Yi Wang

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引用次数: 1

摘要

本文提出的暗网辍学后深度学习算法架构在Nvidia Jetson TX2人工智能板的嵌入式评估板上进行了移植。本文利用后训练结果实现边缘计算的实际道路测试。本设计为安全驾驶行为修改系统提供了车辆的准确识别、交通灯状态前信号、道路限速标志、车辆位置等。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Design and Implementation of Edge Computing for Detection on Embedded Electromobility

The proposed algorithm architecture of deep learning after darknet dropout are porting on embedded evaluation board with artificial intelligence board of Nvidia Jetson TX2. This article uses the post-training results to implement the actual road testing of edge computing. This design presents accurate identification of vehicles, front signal of traffic light status, road speed limit signs, and vehicle location for safe driving behavior modification system.

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来源期刊

2021 4th International Conference on Artificial Intelligence for Industries (AI4I)

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