An Efficient Method of Detection and Recognition in Remote Sensing Image Based on multi-angle Region of Interests

Presently, deep learning technology has been widely used in the field of image recognition. However, it mainly aims at the recognition and detection of ordinary pictures and common scenes. As special images, remote sensing images have different shooting angles and shooting methods compared with ordinary ones, which makes remote sensing images play an irreplaceable role in some areas. In this paper, based on a deep convolution neural network for providing multi-level information of images and combines RPN (Region Proposal Network) for generating multi-angle ROIs (Region of Interest), a new model for object detection and recognition in remote sensing images is proposed. In the experiment, it achieves better results than traditional ways, which demonstrate that the model proposed here would have a huge potential application in remote sensing image recognition.