A very lightweight and efficient image super-resolution network

Author:

Gao DandanORCID,Zhou DengwenORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference50 articles.

1. Deep learning using rectified linear units (relu);Agarap,2018

2. Ahn, N., Kang, B., & Sohn, K.-A. (2018). Fast, accurate, and lightweight super-resolution with cascading residual network. In Proceedings of the European conference on computer vision, vol. 11214 (pp. 256–272). http://dx.doi.org/10.1007/978-3-030-01249-6_16.

3. Densely residual laplacian super-resolution;Anwar;IEEE Transactions on Pattern Analysis and Machine Intelligence,2022

4. Low-complexity single-image super-resolution based on nonnegative neighbor embedding;Bevilacqua,2012

5. Learning a deep convolutional network for image super-resolution;Dong,2014

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