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- W3201842172 abstract "Deep Learning (DL) can be used to model the process of No Reference-Image Quality Assessment (NR-IQA), which has a great contribution to the field of image processing. Even though, a large number of super parameters make the computational complexity gradually increase. Surprisingly, Broad Learning System (BLS) can transform the deep structure of DL into a flat and visual network structure, which reduces the difficulty for practical applications. By applying BLS in NR-IQA, combining the structural and statistical features of the image to reflect the image quality, which expands the research of NR-IQA undoubtedly. In this paper, the mathematical relationship between the image and the score is modeled by BLS, the effectiveness of the proposed method is demonstrated in the numerical experiments." @default.
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- W3201842172 date "2021-01-01" @default.
- W3201842172 modified "2023-09-24" @default.
- W3201842172 title "No-Reference Image Quality Assessment via Broad Learning System" @default.
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- W3201842172 doi "https://doi.org/10.1007/978-3-030-87361-5_14" @default.
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