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Learning Parametric Sparse Models for Image Super-Resolution[NIPS2016][ID2330]
Residual Feature Aggregation Network for Image Super-Resolution
Prakash Kumar | Feasibility of Super Resolution Speech RT-MRI using Deep Learning
255 - Single image super resolution using SRGAN
Lecture 17 - Image Super-Resolution via Iterative Refinement
Enhanced Deep Residual Networks for Single Image Super-Resolution
Single Image Super-Resolution via Sparse Representations - Tomer Peleg
Super-Resolution: Computational and Deep Learning-Based Approaches
953 - MPRNet: Multi-Path Residual Network For Lightweight Single Image Super Resolution
Overview and Attempt to improve Image Super Resolution Methods| SRResNet
[CVPR 2023] Learning Generative Structure Prior for Blind Text Image Super-resolution
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Last Updated: October 21, 2026
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Published at European Conference on Computer Vision, Zurich 2014. Authors: Pranav Jeevan; Akella Srinidhi; Pasunuri Prathiba; Amit Sethi Description: Is it really possible to zoom and enhance This is the spotlight for the paper[ID: 2330]- Authors: Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu Description: Recently, very deep convolutional neural ... PhD student Prakash Kumar speaks at Proc. ISMRM 29th Scientific Session, Online, May 2021, p1782. P Kumar, Y Lim, KS ... Okay so let me explain how the sr3 generates those uh one 발표자: 김희원 (서울대학교 박사과정) 더욱 다양한 영상을 보시려면 NAVER Engineering TV를 참고하세요. Presentation by Majid Rabbani and Prasanna Reddy Pulakurthi on 26 April 2023, as part of the Society for Imaging Science and ... ... and my supervisor angel sappa the paper title is mprnet multipath residual We are students from M.Tech, CSE, IIT Patna. We tried different methods to improve
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