A Remote Sensing Image Key Target Recognition System Design Based on Faster R-CNN
2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE)(2018)
Abstract
Aiming at the problem of traditional low-level recognition of key targets in remote sensing images, a method for target detection and recognition based on Faster R-CNN is proposed. Firstly, the open source remote sensing image data set NWPU VHR-10 dataset is converted into VOC 2007 format as the training sets and test sets. Secondly, according to the training set category information, the hyper-parameters of the neural network are refined, and then the training set is trained using the Faster R-CNN neural network to generate a model. Finally, this model is used to detect unknown remote sensing images and identify important targets. The simulation results show that the method has high recognition accuracy and speed, and can provide reference for recognition of the key targets of remote sensing images.
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Key words
remote sensing image detection,key target recognition,deep learning,convolution neural network,Faster R-CNN
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