利用MLP和相关测量进行车辆检测

Mazouzi Amine, Kerfa Djoudi
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引用次数: 2

摘要

我们的高速公路上越来越多的死亡和破坏,数字令人震惊,这是真实的。2018年,阿尔及利亚有4000多人死于交通事故,其中一半是年轻人。有了这些数字,它不再是一个简单的经典道路安全问题,而是一个自动和精确的道路安全是广泛需要的。我们的工作只是这个问题的一部分,并且在计算机视觉方面首次提供了不同图像处理方法和人工智能的组合。我们的方法旨在准确地检测特定位置的车辆,它是基于学习过程和相关测量方法的结合。在我们的方法中,使用了阶段分离,其中特征提取类型Haar,使用技术子空间减少用于训练阶段的向量的大小,使用人工神经网络的学习过程,最后使用相关测量方法来改进结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicles detection using the MLP and the correlation measurement
More and more deaths and damage in our highways, the numbers are appalling and the finding is real. In 2018, in Algeria more than 4,000 people have been mowed by road accidents, the half of them are young people. With these figures, it is no longer a question of just a simple classic road safety, but an automatic and accurate road safety is widely desired. Our work is just part of this problematic and offers at the first time and in terms of computer vision, a combination of different image processing approaches and artificial intelligence. Our method is designed to exactly detect vehicles in particular locations, it has been made based on a combination of a learning process and a correlation measurement approach. In our method, a secession of phases have been used which, features extraction types Haar, reducing the size of the vectors that were used for the training phase using the technical subspace, a learning procedure using an artificial neural network, and finally to refine the results a correlation measurement approach was performed.
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