An image classification method and system based on enhanced small sample feature decoupling

Abstract

The specification discloses an image classification method and system based on enhanced small sample feature decoupling, aiming to solve the problem that fine-grained features and coarse-grained features cannot be effectively extracted to obtain sufficient local information and global information. The application comprises: based on the to-be-tested data, obtaining enhanced to-be-tested data through a small sample-based data enhancement model; obtaining the enhanced to-be-tested data through a multilayer perceptron and a first classifier; decoupling the enhanced to-be-tested data to obtain fine-grained features and coarse-grained features; connecting the fine-grained features and the coarse-grained features through a feature connector, and classifying based on the connected features through a trained second classifier to obtain a classification prediction result. The application can quickly extract fine-grained features and coarse-grained features, effectively solve the conflict between fine-grained feature extraction and coarse-grained feature extraction, improve the accuracy of image recognition, and solve the problem of insufficient training samples.

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