A vehicle detection method based on deep learning

Abstract

The invention discloses a vehicle detection method based on deep learning, in particular, a method of adding weights of feature maps of the last convolutional layer in a deep network to realize precise vehicle positioning. It belongs to the field of computer vision technology. The present invention first uses the vehicle database to train the deep learning network, then sends the picture to be detected into the trained network, obtains the category information of the picture through a forward propagation, and obtains the weight with the largest weight among the parameters according to the category information, and the last one The feature map of the convolutional layer is superimposed, and then image fusion is performed with the picture to be detected, and finally the accurate positioning of the vehicle is realized. This algorithm has good accuracy and adaptability. It effectively solves the problems of environmental interference, light influence, obstacle influence and low accuracy when traditional image processing algorithms realize vehicle detection, and can be applied to vehicle detection in different scenarios.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a vehicle detection method based on deep learning, which uses the feature map of the last convolutional layer in the deep network to add weights to realize precise positioning of the vehicle. Background technique [0002] In recent years, with the continuous growth of the economy, the number of cars has also continued to increase, which has caused a series of traffic problems. In order to solve these problems, intelligent transportation systems have become a research hotspot. The vehicle detection is the most important link in the intelligent transportation system. Accurate positioning of the vehicle position plays a key role in the research fields of vehicle counting and vehicle classification in the intelligent transportation system. [0003] Currently, vehicle detection algorithms mainly include feature-based vehicle detection algorithms, vision-based vehic...

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Problems solved by technology

[0005] Purpose of the invention: In order to solve the problem that the existing vehicle detection algorithm relies too much on the illumination and quality of the image, so that the vehicle detection has better adaptability and applicability, the present invention provides a vehicle detection method based on deep learning

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