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Li et al., 2019 - Google Patents

FilterNet: Adaptive information filtering network for accurate and fast image super-resolution

Li et al., 2019

View PDF
Document ID
10873105379709563005
Author
Li F
Bai H
Zhao Y
Publication year
Publication venue
IEEE Transactions on Circuits and Systems for Video Technology

External Links

Snippet

Deep convolutional neural network (CNN) approaches have achieved impressive performance for image super-resolution (SR). The main issue of image SR is to effectively recover the high-frequency detail of low-resolution (LR) input. However, existing CNN …
Continue reading at mepro.bjtu.edu.cn (PDF) (other versions)

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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
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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    • G06—COMPUTING; CALCULATING; COUNTING
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