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In view that the existing methods for infrared image super-resolution could not have good performance both in speed and accuracy simultaneously, with the advantage of deep learning method, this paper presents a rapid and accurate infrared image super-resolution method based on zoom mechanism. In the meantime, we design a novel network architecture. First, we take low-resolution images as network inputs...
In recent years, the deep learning method represented by Convolutional Neural Network (CNN) has made great progress in the field of image recognition. In this paper, the representative convolution neural network models such as AlexNet, VGGNet, GoogLeNet, ResNet, DenseNet, SENet and so on are applied to SAR image target recognition. According to the accuracy, parameter quantity, training time and other...
Deep learning has led to impressive performance on a variety of object detection tasks recently. But it is rarely applied in ship detection of SAR images. The paper aims to introduce the detector based on deep learning into this field. We analyze the advantages of the state-of-the-art Faster R-CNN detector in computer vision and limitations in our specific domain. Given this analysis, we proposed...
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