Remote sensing image scene classification method based on scale attention network

Abstract

The invention discloses a remote sensing image scene classification method based on a scale attention network, and the method comprises the steps: randomly dividing a scene data set into a training set and a test set in proportion; then, preprocessing the data set, wherein preprocessing includes image scaling and normalization; inputting the data set into an attention module for significance detection, and generating an attention graph; secondly, initializing scale attention network parameters by using the pre-training model, finely adjusting the scale attention network by using the training set and the attention map, and storing the trained network model; and finally, predicting the category of the to-be-classified image scene by using the fine-tuned scale attention network. According tothe remote sensing image scene classification method based on the scale attention network, the multi-scale attention graph is used for weighting the feature graph for multiple times, the multi-scale image features are extracted and fused, feature representation with enhanced discrimination is generated, and a better effect is achieved in remote sensing image scene classification.

Description

technical field [0001] The invention relates to the technical field of image scene classification in deep learning, in particular to a remote sensing image scene classification method based on a scale attention network. Background technique [0002] In recent years, with the increase of high-resolution remote sensing image data of surface scenes, scene classification of high-resolution remote sensing images has become a research direction of extensive attention, and it is challenging to predict semantic labels of high-resolution remote sensing image scenes by learning feature representations. sex. However, the difficulty of scene classification in high-resolution remote sensing images is that these image scenes have different sizes, colors, poses, and spatial locations in the same category, while image scenes belonging to different categories are similar to each other in many ways. [0003] Recent research results show that deep learning methods have achieved rapid developm...

AI Technical Summary

Problems solved by technology

[0006] In view of this, the present invention provides a remote sensing image scene classification method based on a scale attention network to solve or at least partially solve the technical problem of low classification accuracy existing in the methods in the prior art

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