Image classification method and device, electronic equipment and storage medium

Abstract

The invention relates to an image classification method and device, electronic equipment and a storage medium, relates to the technical field of computers, and is used for solving the problem of relatively low accuracy of an image classification technology in related technologies, and the method comprises the steps: classifying images in a to-be-recognized data set, and determining category labelsof the images in the to-be-recognized data set; extracting text features of each image and text features of the category label of each image, wherein the text features of the images are used for representing the state of an object in the images; determining the matching degree of each image and the corresponding category label according to the text feature of each image and the text feature of the category label of the corresponding image; and determining a target image corresponding to the category label from the images corresponding to the same category label according to the determined matching degree. According to the embodiment of the invention, after the images are classified, the images of the same class label are further screened according to the matching degree of the state of the object in the image and the class label of the image, so that the classification accuracy is improved.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and in particular to an image classification method, device, electronic equipment and storage medium. Background technique [0002] With the rapid development of artificial intelligence, deep learning has been widely used in video images, speech recognition, natural language processing and other related fields. CNN (Convolutional Neural Network, Convolutional Neural Network) is an important branch of deep learning. Due to its super-fitting ability and end-to-end global optimization ability, the accuracy of image classification tasks is greatly improved after applying convolutional neural network. promote. [0003] However, although the accuracy has been improved after using deep learning technology in most scenarios, most of the algorithms cannot directly meet the needs of the business. Take the image classification task as an example. An animal classifier can distinguish the animals...

AI Technical Summary

Problems solved by technology

[0005] The present disclosure provides an image classification method, device, electronic equipment and storage medium to at least solve the problem of low accuracy of image classification technology in the related art

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