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Deep convolutional neural networks have largely benefited computer vision tasks. However, the high computational complexity limits their real-world applications. To this end, many methods have been proposed for efficient network learning, and applications in portable mobile devices. In this paper, we propose a novel Moving-Mobile-Network, named M^2Net, for landmark recognition, equipped each landmark image with located geographic information. We intuitively find that M^2Net can essentiallyarXiv:1912.00418v1 fatcat:svznrlrcsjgbhn5ihu5niyv7mi