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Paper Abstract and Keywords
Presentation 2019-09-19 13:45
Super Resolution for 8K Endoscopic Images Based on Deep Learning
Ayumu Wada, Seiichi Gohshi (Kogakuin Univ)
Abstract (in Japanese) (See Japanese page) 
(in English) Endoscopic operation is performed by inserting a camera through 1 cm holes into the body, and it has a smaller incision and less burden on the patients than open surgeries. 2K/4K endoscope cameras are used in the medical field, and 8K endoscopes have recently been developed to obtain high resolution videos. 8K endoscopes can clearly shoot the condition of the organ surfaces. However, in putting 8K endoscopes into practical use, focusing became a new problem. Although the focus of the 8K endoscopes must be adjusted by a specialist, it is difficult to continue shooting clearly the organ surfaces since manual focusing is not easy. This paper proposes a signal processing method using deep learning to visualize 8K endoscopic videos with insufficient the focus.
Keyword (in Japanese) (See Japanese page) 
(in English) 8K / Endoscopic Videos / Deep Learning / / / / /  
Reference Info. ITE Tech. Rep.
Paper #  
Date of Issue  
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Conference Date 2019-09-19 - 2019-09-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokimeito, Niigata University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IEICE-IE 
Conference Code 2019-09-IE-EMM-LOIS-CMN-ME-AVM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Super Resolution for 8K Endoscopic Images Based on Deep Learning 
Sub Title (in English)  
Keyword(1) 8K  
Keyword(2) Endoscopic Videos  
Keyword(3) Deep Learning  
1st Author's Name Ayumu Wada  
1st Author's Affiliation Kogakuin University (Kogakuin Univ)
2nd Author's Name Seiichi Gohshi  
2nd Author's Affiliation Kogakuin University (Kogakuin Univ)
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Date Time 2019-09-19 13:45:00 
Presentation Time 25 
Registration for IEICE-IE 
Paper #  
Volume (vol) ITE-43 
Number (no)  
#Pages ITE- 
Date of Issue  

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