Deep Residual-Dense Attention Network for Image Super-Resolution

Ding Qin; Xiaodong Gu

doi:10.1007/978-3-030-36802-9_1

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Deep Residual-Dense Attention Network for Image Super-Resolution

Ding Qin Xiaodong Gu

Year: 2019 Communications in computer and information science Pages: 3-10 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-36802-9_1

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Keywords:

Benchmark (surveying) Computer science Residual Focus (optics) Artificial intelligence Channel (broadcasting) Image (mathematics) Resolution (logic) Image resolution High resolution Computer vision Pattern recognition (psychology) Algorithm Telecommunications Remote sensing Cartography Optics Geography

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Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Deep Residual-Dense Attention Network for Image Super-Resolution

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