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Author (up) Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla edit   pdf
url  openurl
  Title Multi-Image Super-Resolution for Thermal Images Type Conference Article
  Year 2022 Publication 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022) Abbreviated Journal  
  Volume 4 Issue Pages 635-642  
  Keywords Thermal Images; Multi-view; Multi-frame; Super-Resolution; Deep Learning; Attention Block  
  Abstract This paper proposes a novel CNN architecture for the multi-thermal image super-resolution problem. In the proposed scheme, the multi-images are synthetically generated by downsampling and slightly shifting the given image; noise is also added to each of these synthesized images. The proposed architecture uses two
attention blocks paths to extract high-frequency details taking advantage of the large information extracted from multiple images of the same scene. Experimental results are provided, showing the proposed scheme has overcome the state-of-the-art approaches.
 
  Address Online; Feb 6-8, 2022  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference VISAPP  
  Notes MSIAU; 601.349 Approved no  
  Call Number Admin @ si @ RSV2022a Serial 3690  
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