Abstract
Deep learning is a deep field of neural networks, and its application in remote sensing image classification and recognition processing has attracted attention and discussion from all walks of life. This paper first briefly introduces the traditional remote sensing image processing methods and the limitations of these algorithms and emphasizes the limitations of these techniques. Then, the research status of target recognition and change detection in remote sensing images based on deep learning is discussed, and how to select and design appropriate deep learning models. And then, the datasets of two different provinces were selected for comparative experiments, and the implementation process of target recognition and change detection in remote sensing images was described in detail. Finally, based on the experimental results, the future trend of deep learning application in remote sensing identification and classification is prospected.
Published Version
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