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- W4280548499 abstract "Remote sensing image change detection is to analyze the change information of two images from the same area at different times. It has wide applications in urban expansion, forest detection, and natural disaster. In this paper, Feature Fusion Network is proposed to solve the problems of slow change detection speed and low accuracy. The MobileNetV3 block is adopted to efficiently extract features and a self-attention module is applied to investigate the relationship between heterogeneous feature maps (image features and concatenated features). The method is tested in data sets SZTAKI and LEVIR-CD. With 98.43 percentage correct classification, it is better than other comparative networks, and its space complexity is reduced by about 50%. The experimental results show that it has better performance and can improve the accuracy or speed of change detection." @default.
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- W4280548499 date "2022-07-21" @default.
- W4280548499 modified "2023-10-16" @default.
- W4280548499 title "Feature fusion network based on siamese structure for change detection" @default.
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- W4280548499 doi "https://doi.org/10.3233/jifs-211432" @default.
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