Image recognition method and device, electronic equipment and computer readable storage medium

Abstract

The embodiment of the invention discloses an image recognition method and device, electronic equipment and a computer readable storage medium. According to the embodiment of the invention, the method includes: after a face image sample is obtained, carrying out spatial feature extraction on the face image sample, training a preset face recognition model based on extracted image features and face label information, obtaining a trained face recognition model, then carrying out domain feature extraction is carried out on the image features, acquiring category features of a face image sample, determining a feature classification result of the face image sample on the basis of the category features and category label information, performing correcting according to the feature classification result and a trained face recognition model, and recognizing a to-be-recognized face image by adopting the corrected face recognition model. According to the scheme, the image recognition efficiency can be improved.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to an image recognition method, device, electronic equipment and computer-readable storage medium. Background technique [0002] With the outbreak of the new coronavirus (COVID-19) around the world, wearing a mask when traveling has become an essential way in daily life. Due to the occlusion of the face by the mask, the collected face images may have facial occlusion. When recognizing this type of face images with facial occlusion, the face recognition model is often trained by matching the features of the face occlusion image and the normal image in the form of weighting or geometric transformation to complete the recognition of the face image. [0003] During the research and practice of the existing technology, the inventors of the present invention found that, for the weighting method, the optimal value of the weight often changes with the change of the data dist...

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Problems solved by technology

[0003] During the research and practice of the existing technology, the inventors of the present invention found that, for the weighting method, the optimal value of the weight often changes with the change of the data distribution, making it impossible to ensure a stable improvement of the face recognition model For the accuracy of face image recognition for face occlusion, for the geometric transformation method, two class centers need to be marked in the face occlusion image and the normal image, which will not only occupy a large amount of video memory, but also in large-scale data training. Greatly increase the time-consuming training of the face recognition model, therefore, the efficiency of image recognition is greatly reduced

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