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Kim et al., 2017 - Google Patents

Deep convolutional neural models for picture-quality prediction: Challenges and solutions to data-driven image quality assessment

Kim et al., 2017

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Document ID
621053759246596053
Author
Kim J
Zeng H
Ghadiyaram D
Lee S
Zhang L
Bovik A
Publication year
Publication venue
IEEE Signal processing magazine

External Links

Snippet

Convolutional neural networks (CNNs) have been shown to deliver standout performance on a wide variety of visual information processing applications. However, this rapidly developing technology has only recently been applied with systematic energy to the …
Continue reading at www.live.ece.utexas.edu (PDF) (other versions)

Classifications

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    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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    • G06K9/4642—Extraction of features or characteristics of the image by performing operations within image blocks or by using histograms
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