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Author Patricia Suarez; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud
Title Near InfraRed Imagery Colorization Type Conference Article
Year 2018 Publication 25th International Conference on Image Processing Abbreviated Journal
Volume Issue Pages 2237 - 2241
Keywords Convolutional Neural Networks (CNN), Generative Adversarial Network (GAN), Infrared Imagery colorization
Abstract (up) This paper proposes a stacked conditional Generative Adversarial Network-based method for Near InfraRed (NIR) imagery colorization. We propose a variant architecture of Generative Adversarial Network (GAN) that uses multiple
loss functions over a conditional probabilistic generative model. We show that this new architecture/loss-function yields better generalization and representation of the generated colored IR images. The proposed approach is evaluated on a large test dataset and compared to recent state of the art methods using standard metrics.
Address Athens; Greece; October 2018
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
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Area Expedition Conference ICIP
Notes MSIAU; 600.086; 600.130; 600.122 Approved no
Call Number Admin @ si @ SSV2018b Serial 3195
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