From 44d3d051839e3f41361ae0d75fde79347e9e8626 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=EC=98=81=EC=A0=9C=20=EC=9E=84?= <iyj0121@ajou.ac.kr>
Date: Fri, 8 Sep 2023 21:03:08 +0900
Subject: [PATCH] Update README.md
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README.md | 12 +++++-------
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diff --git a/README.md b/README.md
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@@ -16,14 +16,12 @@ In addition, this study placed restrictions on convolution using masks when lear
Model �� 2 媛� �ъ슜�섏뿬 SR-reconstruction �� �� �섎㈃ loss 媛믪씠 ��퀬 SR-reconstruction �� �� �덈릺硫� loss 媛믪씠 �믪쑝誘�濡� �섎뱶 �섑뵆�� 吏묒쨷�섎뒗 紐⑤뜽�대떎. �대� �듯븯�� �ш뎄異뺤씠 �섎뱺 �섑뵆�� 吏묒쨷�� �� �덇쾶 �섍퀬,localdetail�� 醫� �� �대┫ �� �덈뒗 怨꾧린濡�(�섎뱶 �섑뵆�� 吏묒쨷�섎뒗 留덉씠�� 湲곕쾿) �숈긽釉붿쓽 �쇱쥌�대떎.
�먰븳 �� �곌뎄�� 紐⑤뜽 �숈뒿�� �� ��, 而⑤낵猷⑥뀡�� 留덉뒪�щ� �ъ슜�섏뿬 �ы븳�� �먯뿀��. �대� �듯븯�� 紐⑤뜽�� �뚯뒪�� �� ��, �대�吏� �ш뎄�깆씠 �섎뒗�� �④낵�곸쑝濡� �곸슜�� �� �덈떎.
-[1] Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee, **"Enhanced Deep Residual Networks for Single Image Super-Resolution,"** <i>2nd NTIRE: New Trends in Image Restoration and Enhancement workshop and challenge on image super-resolution in conjunction with **CVPR 2017**. </i> [[PDF](http://openaccess.thecvf.com/content_cvpr_2017_workshops/w12/papers/Lim_Enhanced_Deep_Residual_CVPR_2017_paper.pdf)] [[arXiv](https://arxiv.org/abs/1707.02921)] [[Slide](https://cv.snu.ac.kr/research/EDSR/Presentation_v3(release).pptx)]
```
-@InProceedings{Lim_2017_CVPR_Workshops,
- author = {Lim, Bee and Son, Sanghyun and Kim, Heewon and Nah, Seungjun and Lee, Kyoung Mu},
- title = {Enhanced Deep Residual Networks for Single Image Super-Resolution},
- booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
- month = {July},
- year = {2017}
+@inproceedings{zhang2018rcan,
+ title={Image Super-Resolution Using Very Deep Residual Channel Attention Networks},
+ author={Zhang, Yulun and Li, Kunpeng and Li, Kai and Wang, Lichen and Zhong, Bineng and Fu, Yun},
+ booktitle={ECCV},
+ year={2018}
}
@inproceedings{Ristea-CVPR-2022,
title={Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection},
--
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