Fine-grained image classification method based on attention transfer mechanism

Abstract

The invention provides a fine-grained image classification method based on an attention transfer mechanism. The fine-grained image classification method is used for improving the classification precision of fine-grained images. The method comprises the following implementation steps: obtaining a training sample set and a test sample set containing fine-grained images, constructing a global perception network model and an attention transfer network model, training the global perception network and the attention transfer network by using the training sample set, and classifying the test sample set by using the trained global perception network and attention transfer network. According to the invention, the global perception network and the attention transfer network are designed to carry outjoint feature extraction on the image; and, on the basis of extracting global features and discriminant region features, the semantic correlation between different discriminant regions is further extracted by the network, so that the feature extraction capability of the network is enhanced, and the classification accuracy of fine-grained images is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision and relates to a fine-grained image classification method, in particular to a fine-grained image classification method based on an attention transfer mechanism, which can be used for fine classification tasks, such as bird classification and car classification. Background technique [0002] Image classification is a processing method that extracts the discriminative features of the image itself through a design-based or learning-based method, so that smart devices can automatically identify the category to which the image subject belongs. Image classification methods are widely used in various fields of society, such as face recognition, species recognition, etc. According to the granularity of the image classification target, image classification methods can generally be divided into two categories, namely general (coarse-grained) image classification and sub-category (fine-grained) image...

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art, and propose a fine-grained image classification met

Images