Image Super-resolution with An Enhanced Group Convolutional Neural Network

  title={Image Super-resolution with An Enhanced Group Convolutional Neural Network},
  author={Chunwei Tian and Yixuan Yuan and Shichao Zhang and Chia-Wen Lin and Wangmeng Zuo and David Zhang},
  journal={Neural networks : the official journal of the International Neural Network Society},
CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image super-resolution, which may increase computational cost in general. In this paper, we present an enhanced super-resolution group CNN (ESRGCNN) with a shallow architecture by fully fusing deep and wide channel features to extract more accurate low-frequency information in terms of correlations of different channels in… 

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  • Alain HoréD. Ziou
  • Computer Science
    2010 20th International Conference on Pattern Recognition
  • 2010
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