Survey of the Image Recognition Based on Deep Learning Network for Autonomous Driving Car

Jin Liu
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引用次数: 2

Abstract

Recently, autonomous driving car is a hot area of research and the image recognition technology is one of the key technologies for autonomous driving cars to drive safely on the road. With the development of times and technology, deep learning has been widely applied in image recognition technology, and it plays an important role in this field. In this paper, the development of image recognition technology in autonomous driving cars and deep learning are introduced. Different models of deep learning networks, such as Deep Neural Network (DNN), Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) are also analyzed. In addition, the theoretical basis of deep learning in image recognition are summarized and the applications of deep learning in image recognition are carried out. Finally, the paper will look into the future development of autonomous vehicles and the future of image recognition technology. It is concluded that, image recognition system, based on deep learning network has been widely used in autonomous driving cars at present, and it has a prospective future for further development.
基于深度学习网络的自动驾驶汽车图像识别研究
近年来,自动驾驶汽车是一个研究热点,图像识别技术是自动驾驶汽车在道路上安全行驶的关键技术之一。随着时代和技术的发展,深度学习在图像识别技术中得到了广泛的应用,并在该领域发挥着重要的作用。本文介绍了自动驾驶汽车图像识别技术和深度学习技术的发展。分析了深度学习网络的不同模型,如深度神经网络(DNN)、循环神经网络(RNN)和卷积神经网络(CNN)。此外,总结了深度学习在图像识别中的理论基础,并进行了深度学习在图像识别中的应用。最后,本文将展望自动驾驶汽车的未来发展和图像识别技术的未来。综上所述,基于深度学习网络的图像识别系统目前已经在自动驾驶汽车上得到了广泛的应用,具有广阔的发展前景。
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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