使用图像处理和深度学习的自动驾驶机器人汽车

Duong Dinh Tu, Phan Xuan Hieu, Hoang Tuan Hiep
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引用次数: 0

摘要

在图像处理领域,图像识别是近年来研究人员面临的主要挑战之一。识别的目标是检测和提取图像中的特征,将样本划分到不同的层。在这个领域,一个非常有趣的问题是使用图像处理的自动驾驶机器人汽车。本研究的目的是提出一种深度学习方法来解决机器人的路径识别问题。基于卷积神经网络构建自动驾驶机器人模型,使用不同的层自动提取图像中的最佳特征。实验结果表明,该方法具有较低的误差率
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-driving robot cars using image processing and deep learning
In the field of image processing, image recognition is one of the major challenges for researchers in recent years. The goal of recognition is to detect and extract features in the images to classify samples into different layers. One problem of great interest in this field is self-driving robot cars using image processing. The aim of this research is to present a deep learning method to solve the path recognition matter for robots. A self-driving robot model will be built based on the convolutional neural network with the use of different layers to automatically extract the best features in the image. Experimentation procedure has been carried out and results with low error rates had been obtained
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