A Scale Adaptive Convolutional Neural Network for Object Detection in Remote Sensing Images
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Abstract
A new approach based on convolutional neural network (CNN) is proposed to improve the accuracy of multi-object in remote sensing images. Faster region convolutional neural network has been employed as the basic framework. Moreover, a scale adaptive convolutional neural network (SA-CNN) is proposed to deal with the multi-scale target detection in remote sensing images. The comparative experimental results show that the proposed SA-CNN significantly improves the accuracy of multi-object detection.
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