Convolutional neural network-based method for recognizing targets in front of vehicles
A convolutional neural network and target recognition technology, applied in biological neural network models, neural architecture, character and pattern recognition, etc., can solve the problem of inability to guarantee the recognition success rate, and achieve the effect of strong environmental adaptability and high recognition rate
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[0040] refer to figure 1 , a vehicle front target recognition method based on convolutional neural network, the steps are as follows:
[0041] Step 1. Sample acquisition and image processing
[0042] 1) Acquire target samples in front of the vehicle: Obtain images from public datasets of vehicle recognition algorithms such as vehicle detection, vehicle tracking, and semantic segmentation. Part of the images are used as original training samples, and the rest are used as original test samples.
[0043] The data used for training and testing are MIT (Massachusetts Institute of Technology, Massachusetts Institute of Technology) data and KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute, computer vision algorithm evaluation platform) data sets published on the Internet. The original training samples are 2000 images with a size of 50*50 pixels, and the object to be recognized is in the center of the image. The original test samples are 500 images with a ...
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