基于边缘计算的生成对抗网络用于实时道路感知

Yiting He, Xiaoyi Fan, Feng Wang, Fangxin Wang, Jiangchuan Liu
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引用次数: 4

摘要

汽车已经成为现代生活的必需品之一,并深入到我们的日常生活中。不幸的是,它们也带来了许多社会问题,其中交通事故是最臭名昭著的威胁汽车司机和其他道路使用者。先进驾驶辅助系统(ADAS)是近年来发展迅速的一种技术,它可以减少甚至消除驾驶员的失误,极大地减轻驾驶员的痛苦或压力。这些先进的ADAS主要依靠内置摄像头、雷达和超声波传感器为目标检测提供道路传感服务,最近视觉和神经网络技术的爆炸式发展进一步推动了这些服务的发展。
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Edge Computing Empowered Generative Adversarial Networks for Realtime Road Sensing
Automobiles have become one of the necessities of modern life and deeply penetrated into our daily activities. They unfortunately also introduce numerous social problems, among which traffic accidents are most notoriously threatening automobile drivers and other road users. Advanced driver-assistance systems (ADAS) are under rapid development in recent years, which can necessarily reduce or even eliminate the driver errors, significantly relieving on drivers suffering or stress. These state-of-the-art ADAS mainly rely on built-in cameras, radars and ultrasound sensors to provide road sensing services for object detection, which are further advanced by recent explosion of vision and neural network technologies.
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