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Image quality assessment: Learning to rank image distortion level

Publication ,  Journal Article
Faigenbaum-Golovin, S; Shimshi, O
Published in: Electronic Imaging
January 16, 2022

Duke Scholars

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Published In

Electronic Imaging

DOI

EISSN

2470-1173

Publication Date

January 16, 2022

Volume

34

Issue

9

Publisher

Society for Imaging Science & Technology
 

Citation

APA
Chicago
ICMJE
MLA
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Faigenbaum-Golovin, S., & Shimshi, O. (2022). Image quality assessment: Learning to rank image distortion level. Electronic Imaging, 34(9). https://doi.org/10.2352/ei.2022.34.9.iqsp-386
Faigenbaum-Golovin, Shira, and Or Shimshi. “Image quality assessment: Learning to rank image distortion level.” Electronic Imaging 34, no. 9 (January 16, 2022). https://doi.org/10.2352/ei.2022.34.9.iqsp-386.
Faigenbaum-Golovin S, Shimshi O. Image quality assessment: Learning to rank image distortion level. Electronic Imaging. 2022 Jan 16;34(9).
Faigenbaum-Golovin, Shira, and Or Shimshi. “Image quality assessment: Learning to rank image distortion level.” Electronic Imaging, vol. 34, no. 9, Society for Imaging Science & Technology, Jan. 2022. Crossref, doi:10.2352/ei.2022.34.9.iqsp-386.
Faigenbaum-Golovin S, Shimshi O. Image quality assessment: Learning to rank image distortion level. Electronic Imaging. Society for Imaging Science & Technology; 2022 Jan 16;34(9).

Published In

Electronic Imaging

DOI

EISSN

2470-1173

Publication Date

January 16, 2022

Volume

34

Issue

9

Publisher

Society for Imaging Science & Technology