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Poster
NEAR INFRARED IMAGERY COLORIZATION
- Citation Author(s):
- Submitted by:
- Patricia Suarez
- Last updated:
- 4 October 2018 - 7:21pm
- Document Type:
- Poster
- Document Year:
- 2018
- Event:
- Presenters:
- Patricia L. Suarez
- Paper Code:
- ICIP18001
- Categories:
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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.
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ESPOL POLYTHECNIC GUAYAQUIL
ESPOL POLYTHECNIC GUAYAQUIL-ECUADOR