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The popular deep learning method of the year established a recognition model to identify remote sensing images, which is a new method. Based on Google Inc.’s Inception-v3 convolutional neural network recognition model, this paper adopted a conception of migration learning to achieve the accurate automatic classification of remote sensing image scenes. Since the model already possesses good convolution parameters for image feature extraction, the idea of migration learning was used to retrain the model. To achieve the purpose of learning UC Merced Land Use Dataset related data types, the authors use the training set and test set to test separately. The learning model has a good learning effect and a high classification recognition rate.

An Improved Remote Sensing Image Classification Method Based on DCNN