Dynamic Depth-Aware Network for Endoscopy Super-Resolution
Author:
Affiliation:
1. Department of Electrical Engineering, City University of Hong Kong, Hong Kong
2. Department of Endoscopic Surgery, the sixth Affiliated Hospital, Sun Yat-sen Univerisity, China
Funder
National Natural Science Foundation of China
Hong Kong Research Grants Council
Hong Kong RGC Collaborative Research Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics
Link
http://xplorestaging.ieee.org/ielx7/6221020/9910251/09815859.pdf?arnumber=9815859
Reference51 articles.
1. Light Field Image Super-Resolution Using Deformable Convolution
2. Stereo correspondence and reconstruction of endoscopic data challenge;allan;arXiv 2101 01133,2021
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4. ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
5. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
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