Image classification method, device, computer equipment and storage medium

Abstract

The present application relates to an image classification method, device, computer equipment and storage medium. The method includes: acquiring an image to be classified; classifying the image to be classified by using a preset classification model to obtain the categories to which a plurality of different attributes of the image to be classified belong; the image to be classified is geometrically corrected image; the classification model adopts attention mechanism for the image to be classified and performs multi-task processing. Using this method can improve the accuracy of image classification.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to an image classification method, device, computer equipment and storage medium. Background technique [0002] With the rapid development of science and technology, artificial intelligence technology has been widely used in people's life and work, especially for image recognition and processing has an irreplaceable position. [0003] Taking face image recognition as an example, computer equipment can use traditional neural network models to recognize and classify face images, so that it can distinguish whether glasses are worn in face images, or whether the mouth is closed or not. [0004] However, the traditional neural network model is usually a multi-layer convolutional neural network model. Using this model to identify the attributes of face images, the recognition results are not accurate. Contents of the invention [0005] Based on this, it is necessary to prov...

AI Technical Summary

Problems solved by technology

[0004] However, the traditional neural network model is usually a multi-layer convolutional neural network model. Using this model to identify the attributes of face images, the recognition results are not accurate.

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