02-06-2023 дата публикации
Номер: CN116206327A
Принадлежит:
The invention relates to the technical field of image classification, and discloses an image classification method based on online knowledge distillation, which comprises the steps of inputting images to be classified, calibrating portraits in image data, constructing a training image set, extracting global features of the images, superposing local features in the global features, and constructing a plurality of equal network frameworks. The method comprises the steps of constructing an integrated teacher model, aligning probability distribution between the integrated teacher model and equivalent networks, introducing a feature embedding space, obtaining a total comparison loss function under M equivalent networks, introducing a weight factor to obtain a total loss function of a classification model, bringing a data set into a training number set for training, and obtaining an image classification result. The method comprises the following steps: extracting a local feature region, independently ...
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