Semantically accurate super-resolution Generative Adversarial Networks

Tristan Frizza; Donald G. Dansereau; Nagita Mehr Seresht; Michael Bewley

doi:10.1016/j.cviu.2022.103464

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Semantically accurate super-resolution Generative Adversarial Networks

Tristan Frizza Donald G. Dansereau Nagita Mehr Seresht Michael Bewley

Year: 2022 Journal: Computer Vision and Image Understanding Vol: 221 Pages: 103464-103464 Publisher: Elsevier BV

DOI: 10.1016/j.cviu.2022.103464

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Keywords:

Computer science Artificial intelligence Segmentation Aerial image Generative grammar Adversarial system Feature (linguistics) Domain (mathematical analysis) Task (project management) Computer vision Image resolution Image (mathematics) Generative adversarial network Image segmentation Resolution (logic) Pattern recognition (psychology)

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Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Signal Denoising Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Semantically accurate super-resolution Generative Adversarial Networks

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