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Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification
[article]
2020
arXiv
pre-print
Remote sensing image scene classification is a fundamental but challenging task in understanding remote sensing images. Recently, deep learning-based methods, especially convolutional neural network-based (CNN-based) methods have shown enormous potential to understand remote sensing images. CNN-based methods meet with success by utilizing features learned from data rather than features designed manually. The feature-learning procedure of CNN largely depends on the architecture of CNN. However,
arXiv:2001.09614v1
fatcat:drfzcrelbrhgngujdgrk3uu2ee