An image detection method and system based on a convolutional neural network

Abstract

The invention discloses an image detection method and system based on a convolutional neural network, and the method comprises the following steps of collecting and obtaining a preset number of labeled sample images, and carrying out the preprocessing of the labeled sample images, and obtaining a denoised target area image with a label; performing feature extraction on each labeled target area image to obtain a 3D feature matrix of each labeled target area; training the 3D convolutional neural network weak entity detection model by using all the obtained 3D feature matrixes to obtain a trained3D convolutional neural network weak entity detection model; and performing preprocessing and feature extraction on the to-be-detected picture to obtain a 3D feature matrix of the to-be-detected picture, inputting the 3D feature matrix of the to-be-detected picture into the trained 3D convolutional neural network weak entity detection model, and outputting a detection result of the to-be-detectedpicture, so that the weak entity target detection can be completed more accurately and quickly.

Description

technical field [0001] The invention belongs to the technical field of image detection, in particular to an image detection method and system based on a convolutional neural network. Background technique [0002] Object detection task is an extremely important part of image processing tasks. Now it is mainly divided into two categories: human detection and algorithm detection. Manual detection is time-consuming and laborious, and its efficiency and accuracy are relatively low. In algorithm detection: one method is to use 2D image information to make independent predictions, but a lot of information about the relationship between image sequences will be missing, resulting in lower prediction accuracy; the other method is to use a single 3D network structure For prediction, it can achieve better results in simple target detection tasks in natural images, but in the detection process for weak entities with inconspicuous features and relatively small sizes, the detection effic...

AI Technical Summary

Problems solved by technology

According to the target detection algorithm in the convolutional neural network, the present invention proposes an image detection method for the problem of weak entity detection, which can complete the detection of weak entity targets more accurately and quickly; the present invention constructs the model of the convolutional neural network, It can make up for the shortcomings of using a general model for weak entity detection, and can solve the problem of difficult detection caused by unobvious features and relatively small sizes in the process of weak entity detection

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