Multi-scale target detection method based on deep convolutional neural network
A neural network and deep convolution technology, applied in the field of computer image processing, can solve the problems of low accuracy of small-scale objects, reduced robustness and effectiveness, loss of small-scale object features, etc.
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[0068] The present invention will be further described below in conjunction with specific examples.
[0069] like figure 1 As shown, the multi-scale target detection method based on deep convolutional neural network provided in this embodiment, its specific situation is as follows:
[0070] Step 1. Obtain the highway video dataset, then obtain its video frames, manually mark them, and divide them into training datasets and verification datasets.
[0071] Step 2, converting the image and label data of the image dataset into the format required for training the deep convolutional neural network through preprocessing, including the following steps:
[0072] In step 2.1, the image in the dataset is scaled to a size of 768×1344 pixels in length and width, and the label data is also scaled to the corresponding size according to the corresponding ratio.
[0073] In step 2.2, in the scaled image, randomly crop the place containing the label to obtain a square image with a size of 76...
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