Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384304013> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W4384304013 endingPage "1" @default.
- W4384304013 startingPage "1" @default.
- W4384304013 abstract "Image quality assessment (IQA) has always been a popular research topic. There have been many methods proposed for predicting image quality, also known as the mean opinion score (MOS). However, it is worth noting that different people may assign different opinion scores to the same image. Image quality described by all subjective opinion scores can express rich subjective information about the image, such as diversity and uncertainty, which cannot be accurately described by a single MOS. Therefore, this paper proposes a fuzzy neural network to predict the opinion score distribution (OSD) of image quality. The fuzzy neural network includes three sub-networks: a feature extraction network, a feature fuzzification network, and a fuzzy learning network. First, a novel network is designed to extract image features. The extracted features are then fuzzified by fuzzy theory to model the epistemic uncertainty in the feature extraction process. Finally, the OSD of image quality is predicted using the fuzzy learning network by learning the mapping from fuzzy features to fuzzy uncertainty when rating image quality. In addition, to train the proposed fuzzy neural network, we employ a new loss function based on the quantile and the cumulative density function. We experimentally validate the feasibility and superiority of the proposed method in two aspects. On the one hand, we demonstrate the performance of the proposed method in predicting the OSD of image quality on the SJTU IQSD and KonIQ-10K databases. On the other hand, we also prove the feasibility of the proposed method in predicting the MOS of image quality on several popular IQA databases, including CSIQ, TID2013, LIVE MD, and LIVE Challenge." @default.
- W4384304013 created "2023-07-15" @default.
- W4384304013 creator A5018856552 @default.
- W4384304013 creator A5034718093 @default.
- W4384304013 creator A5043405654 @default.
- W4384304013 creator A5064168853 @default.
- W4384304013 creator A5089960389 @default.
- W4384304013 date "2023-01-01" @default.
- W4384304013 modified "2023-10-18" @default.
- W4384304013 title "Blind Image Quality Assessment: A Fuzzy Neural Network for Opinion Score Distribution Prediction" @default.
- W4384304013 doi "https://doi.org/10.1109/tcsvt.2023.3295375" @default.
- W4384304013 hasPublicationYear "2023" @default.
- W4384304013 type Work @default.
- W4384304013 citedByCount "0" @default.
- W4384304013 crossrefType "journal-article" @default.
- W4384304013 hasAuthorship W4384304013A5018856552 @default.
- W4384304013 hasAuthorship W4384304013A5034718093 @default.
- W4384304013 hasAuthorship W4384304013A5043405654 @default.
- W4384304013 hasAuthorship W4384304013A5064168853 @default.
- W4384304013 hasAuthorship W4384304013A5089960389 @default.
- W4384304013 hasConcept C105795698 @default.
- W4384304013 hasConcept C115961682 @default.
- W4384304013 hasConcept C118671147 @default.
- W4384304013 hasConcept C119857082 @default.
- W4384304013 hasConcept C124101348 @default.
- W4384304013 hasConcept C127413603 @default.
- W4384304013 hasConcept C138885662 @default.
- W4384304013 hasConcept C153180895 @default.
- W4384304013 hasConcept C154945302 @default.
- W4384304013 hasConcept C176217482 @default.
- W4384304013 hasConcept C21547014 @default.
- W4384304013 hasConcept C2776401178 @default.
- W4384304013 hasConcept C33923547 @default.
- W4384304013 hasConcept C41008148 @default.
- W4384304013 hasConcept C41895202 @default.
- W4384304013 hasConcept C42011625 @default.
- W4384304013 hasConcept C50644808 @default.
- W4384304013 hasConcept C52622490 @default.
- W4384304013 hasConcept C5263885 @default.
- W4384304013 hasConcept C55020928 @default.
- W4384304013 hasConcept C58166 @default.
- W4384304013 hasConcept C62897895 @default.
- W4384304013 hasConceptScore W4384304013C105795698 @default.
- W4384304013 hasConceptScore W4384304013C115961682 @default.
- W4384304013 hasConceptScore W4384304013C118671147 @default.
- W4384304013 hasConceptScore W4384304013C119857082 @default.
- W4384304013 hasConceptScore W4384304013C124101348 @default.
- W4384304013 hasConceptScore W4384304013C127413603 @default.
- W4384304013 hasConceptScore W4384304013C138885662 @default.
- W4384304013 hasConceptScore W4384304013C153180895 @default.
- W4384304013 hasConceptScore W4384304013C154945302 @default.
- W4384304013 hasConceptScore W4384304013C176217482 @default.
- W4384304013 hasConceptScore W4384304013C21547014 @default.
- W4384304013 hasConceptScore W4384304013C2776401178 @default.
- W4384304013 hasConceptScore W4384304013C33923547 @default.
- W4384304013 hasConceptScore W4384304013C41008148 @default.
- W4384304013 hasConceptScore W4384304013C41895202 @default.
- W4384304013 hasConceptScore W4384304013C42011625 @default.
- W4384304013 hasConceptScore W4384304013C50644808 @default.
- W4384304013 hasConceptScore W4384304013C52622490 @default.
- W4384304013 hasConceptScore W4384304013C5263885 @default.
- W4384304013 hasConceptScore W4384304013C55020928 @default.
- W4384304013 hasConceptScore W4384304013C58166 @default.
- W4384304013 hasConceptScore W4384304013C62897895 @default.
- W4384304013 hasLocation W43843040131 @default.
- W4384304013 hasOpenAccess W4384304013 @default.
- W4384304013 hasPrimaryLocation W43843040131 @default.
- W4384304013 hasRelatedWork W2016461833 @default.
- W4384304013 hasRelatedWork W2120911984 @default.
- W4384304013 hasRelatedWork W2136489243 @default.
- W4384304013 hasRelatedWork W2379864843 @default.
- W4384304013 hasRelatedWork W2382379241 @default.
- W4384304013 hasRelatedWork W2546942002 @default.
- W4384304013 hasRelatedWork W2751066217 @default.
- W4384304013 hasRelatedWork W2811390910 @default.
- W4384304013 hasRelatedWork W4304098873 @default.
- W4384304013 hasRelatedWork W805523833 @default.
- W4384304013 isParatext "false" @default.
- W4384304013 isRetracted "false" @default.
- W4384304013 workType "article" @default.