Patricia L. Suarez, Angel D. Sappa, Boris X. Vintimilla, & Riad I. Hammoud. (2018). Near InfraRed Imagery Colorization. In 25 th IEEE International Conference on Image Processing, ICIP 2018 (pp. 2237–2241).
Abstract: 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.1
Index Terms—Convolutional Neural Networks (CNN), Generative
Adversarial Network (GAN), Infrared Imagery colorization.
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Patricia L. Suarez, Angel D. Sappa, Boris X. Vintimilla, & Riad I. Hammoud. (2019). Image Vegetation Index through a Cycle Generative Adversarial Network. In Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States (pp. 1014–1021).
Abstract: This paper proposes a novel approach to estimate the
Normalized Difference Vegetation Index (NDVI) just from
an RGB image. The NDVI values are obtained by using
images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The
cycled GAN network is able to obtain a NIR image from
a given gray scale image. It is trained by using unpaired
set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are
obtained from the provided RGB images). Then, the NIR
image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous
approaches are also provided.
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Patricia Pasmay Bohorquez, A. R. R., Homero Ojeda Guevara, Sixifo Falcones. (2024). Transmission Expansion Planning with Photovoltaic Generation Penetration. In 13th International Conference on Renewable Energy Research and Applications.
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Patricia Suarez & Angel D. Sappa. (2024). Haze-Free Imaging through Haze-Aware Transformer Adaptations. In Lecture Notes in Networks and Systems: 4th International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) (Vol. Vol. 1116 LNNS, pp. 27–37).
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Patricia Suarez & Angel D. Sappa. (2025). Synthetic Thermal Image Generation from Multi-Cue Input Data. 20th International Conference on Computer Vision Theory and Applications VISIGRAPP 2025 Porto 26-28 Febrero 2025, Vol. 3, 275–282.
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Patricia Suarez & Angel D. Sappa. (2025). Lightweight Architecture for Fruit Quality Estimation in the Infrared Domain. In 5th International Conference on Innovations in Computational Intelligence and Computer Vision ICICV 2025.
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Patricia Suarez & Angel Sappa. (2023). Toward a thermal image-like representation. In Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) Lisbon, 19-21 Febrero 2023 (pp. 133–140).
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Patricia Suarez Riofrio & Angel D. Sappa. (2025). Thermal Image Synthesis: Bridging the Gap between Visible and Infrared Spectrum. In Lecture Notes in Computer Science. 19th International Symposium on Visual Computing ISVC 2024 Lake Tahoe 21-23 Octubre 2024 (Vol. Vol. 15046 LNCS, 384–396).
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Patricia Suarez, A. D. S. (2024). A Generative Model for Guided Thermal Image Super-Resolution. In 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2024 Rome 27 – 29 Febraury 2024 (Vol. Vol. 3: VISAPP, pp. 765–771).
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Patricia Suarez, A. S. (2024). Depth-Conditioned Thermal-like Image Generation. In 14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024.
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