Deep Learning Method for Building Image Localization in Smart City

In recent years, with the construction and development of smart cities, the rapid popularization of the Internet of Things and the sharp increase of Internet users, a large amount of multimedia data with geo-location information shared by users has emerged.However, only a small part of the image data is used correctly.Therefore, building detection can not only realize geographic positioning, but also has guiding significance for GIS mapping and automatic updating.With the extensive application of convolutional neural network and cyclic neural network in image processing, this paper proposes that the BFPN-RCNN algorithm can be used to recognize the curved buildings in the image.By comparing with other image detection algorithms on different data sets, it is proved that the proposed algorithm can effectively locate curved images in natural scene images.