Image target detection method based on convolutional neural network

Abstract

The invention discloses an image target detection method based on a convolutional neural network, and the method comprises the following steps: carrying out the preprocessing of a data set, and employing a data enhancement method; a Mosaic data enhancement method is used for data, and four random pictures are spliced together to improve the data training effect; a basic convolutional neural network is constructed by referring to YOLOv2, each convolution unit comprises a convolution layer, a BatchNormalization layer and a Relu activation layer, no full connection layer exists in the whole network structure, and the convolution layers are completely used; a residual network structure is used in the convolutional neural network, so that the depth of the network can be deepened, and a better feature is provided for model learning; multi-scale feature map fusion is used to improve the detection effect of a network model on images of different scales, and the robustness of a target detection model is improved; data annotation is made after data enhancement, then clustering analysis is performed on bounding boxes in a training set by using a clustering method, and a proper prior box is selected according to a clustering analysis result, so that model learning is facilitated.

Description

technical field [0001] The invention belongs to the fields of artificial intelligence, deep learning and computer vision, and is an image target detection method based on a convolutional neural network. It draws on some experiences in the field of target detection and builds a convolutional neural network to provide an image target detection method based on a convolutional neural network. Methods in the field of image object detection. Background technique [0002] Image object detection is an important application of artificial intelligence in the field of computer vision. Now the deep learning model has replaced the traditional machine vision method and has become the mainstream solution in the field of target detection. Generally speaking, target detection usually focuses on a specific object target, and requires both the category information and location information of this target. We need to separate the target of interest from the background and determine the descript...

AI Technical Summary

Problems solved by technology

[0005] In the target detection network, the size of the target to be detected is different, and it is relatively easy to detect a larger target, but for a smaller target, it is easy to lose features in the process of network downsampling, and the detection is difficult. Occurs frequently

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