SUR-FeatNet: Predicting the satisfied user ratio curve for image compression with deep feature learning
- Submitting institution
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De Montfort University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12113
- Type
- D - Journal article
- DOI
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10.1007/s41233-020-00034-1
- Title of journal
- Quality and User Experience
- Article number
- 5
- First page
- -
- Volume
- 5
- Issue
- -
- ISSN
- 2366-0139
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2020
- URL
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- Supplementary information
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-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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6
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This journal article is an extended version of a conference paper presented at Eleventh International Conference on Quality of Multimedia Experience (QoMEX 2019). The conference paper was selected and invited to be submitted to a Topical Collection of the journal by the best paper award committee. The research, which is a collaboration between DMU, University of Konstanz, and Chinese Academy of Science, was partially funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 251654672–TRR 161 (Project A05). The collaboration led to the joint organisation of a related workshop at IEEE ICME 2020.
- Author contribution statement
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- Non-English
- No
- English abstract
- -