End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks
IEEE ACCESS, pp. 31959.0-31970.0, 2019.
In this paper, we propose a new image super-resolution (SR) approach based on a convolutional neural network (CNN), which jointly learns the feature extraction, upsampling, and high-resolution (HR) reconstruction modules, yielding a completely end-to-end trainable deep CNN. However, directly training such a deep network in an end-to-end f...More
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