No-Reference Quality Assessment is a type of image quality assessment method that estimates perceptual quality without access to the original reference image, relying solely on the distorted image for evaluation.
486
Publications
52.5K
Citations
1.2K
Authors
406
Institutions
Publications per year
2017–2026
265
Variants
Nr-qa
Parents
Publications
486
Convolutional Neural Networks for No-Reference Image Quality Assessment
1–5 of 486
Authors
1.2K
- AC
25
h-index
- WL
24
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- GZ
22
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- KG
18
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- XY
14
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1–5 of 1.2K
Institutions
406
Nanyang Technological University
Singapore, Singapore
26 h-index
44 publications
6.5K citations
The University of Texas at Austin
Austin, United States
25 h-index
62 publications
55.8K citations
Shanghai Jiao Tong University
Shanghai, China
24 h-index
131 publications
15.7K citations
Xidian University
Xi'an, China
21 h-index
67 publications
4.8K citations
Tianjin University
Tianjin, China
17 h-index
54 publications
2.8K citations
City University of Hong Kong
Hong Kong, Hong Kong
15 h-index
44 publications
2.9K citations
Ningbo University
Ningbo, China
14 h-index
52 publications
2.2K citations
Peking University
Beijing, China
13 h-index
31 publications
2.8K citations
1–8 of 406
Venues
- IEEE Transactions on Image Processing
40 publications · 16.4K citations
33
h-index
- IEEE Transactions on Multimedia
25 publications · 2.4K citations
22
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- IEEE Transactions on Circuits and Systems for Video Technology
21 publications · 1.4K citations
19
h-index
- IEEE Signal Processing Letters
19 publications · 9.6K citations
17
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- IEEE Transactions on Broadcasting
15 publications · 931 citations
15
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