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Author |
Rafael E. Rivadeneira, Henry O. Velesaca, Angel D. Sappa |
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Title |
Object Detection in Very Low-Resolution Thermal Images through a Guided-Based Super-Resolution Approach |
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2023 |
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17th International Conference On Signal Image Technology & Internet Based System |
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cidis @ cidis @ |
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224 |
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Author |
Rafael E. Rivadeneira, Angel Domingo Sappa, Vintimilla B. X. and Hammoud R. |
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Title |
A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. |
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Journal Article |
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Year |
2022 |
Publication |
Sensors |
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Sensors |
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Vol. 22 |
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Issue 6 |
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no |
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cidis @ cidis @ |
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170 |
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Author |
Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al. |
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Title |
Thermal Image Super-Resolution Challenge Results- PBVS 2022. |
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Conference Article |
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Year |
2022 |
Publication |
Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
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CONFERENCE |
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2022-June |
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349-357 |
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This paper presents results from the third Thermal Image
Super-Resolution (TISR) challenge organized in the Perception Beyond the Visible Spectrum (PBVS) 2022 workshop.
The challenge uses the same thermal image dataset as the
first two challenges, with 951 training images and 50 validation images at each resolution. A set of 20 images was
kept aside for testing. The evaluation tasks were to measure
the PSNR and SSIM between the SR image and the ground
truth (HR thermal noisy image downsampled by four), and
also to measure the PSNR and SSIM between the SR image
and the semi-registered HR image (acquired with another
camera). The results outperformed those from last year’s
challenge, improving both evaluation metrics. This year,
almost 100 teams participants registered for the challenge,
showing the community’s interest in this hot topic. |
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cidis @ cidis @ |
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175 |
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Author |
Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Chenyang Wang, Junjun Jiang, Xianming Liu, Zhiwei Zhong, Dai Bin, Li Ruodi, Li Shengye |
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Title |
Thermal Image Super-Resolution Challenge Results – PBVS 2023 |
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Conference Article |
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Year |
2023 |
Publication |
19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition CVPR 2023, junio 18-28 |
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2023-June |
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470 - 478 |
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21607508 |
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979-835030249-3 |
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Call Number |
cidis @ cidis @ |
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210 |
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Author |
Rafael E. Rivadeneira, Angel D. Sappa and Boris X. Vintimilla |
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Title |
Multi-Image Super-Resolution for Thermal Images. |
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Conference Article |
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Year |
2022 |
Publication |
Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 |
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4 |
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635 - 642 |
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no |
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cidis @ cidis @ |
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181 |
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Author |
Pereira J., Mora M. & W. Agila |
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Title |
Qualitative Model to Maximize Shrimp Growth at Low Cost |
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Journal Article |
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Year |
2021 |
Publication |
5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
167 |
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Author |
Patricia Suarez, Henry Velesaca, Dario Carpio, Angel Sappa, Patricia Urdiales, Francisca Burgos |
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Title |
Deep Learning based Shrimp Classification |
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Conference Article |
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Year |
2022 |
Publication |
17th International Symposium on Visual Computing, San Diego, USA, Octubre 3-5. Lecture Notes in Computer Science (LNCS) |
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13598 LNCS |
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36-45 |
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Call Number |
cidis @ cidis @ |
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194 |
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Author |
Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa |
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Title |
Corn Kernel Classification From Few Training Samples |
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Journal Article |
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Year |
2023 |
Publication |
In journal Artificial Intelligence in Agriculture |
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Vol. 9 |
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pp. 89-99 |
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25897217 |
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Call Number |
cidis @ cidis @ |
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223 |
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Author |
Patricia Suarez & Angel Sappa |
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Title |
Toward a thermal image-like representation |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 |
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133 - 140 |
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Call Number |
cidis @ cidis @ |
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205 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud |
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Title |
Near InfraRed Imagery Colorization |
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Conference Article |
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Year |
2018 |
Publication |
25 th IEEE International Conference on Image Processing, ICIP 2018 |
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2237-2241 |
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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.1
Index Terms—Convolutional Neural Networks (CNN), Generative
Adversarial Network (GAN), Infrared Imagery colorization. |
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gtsi @ user @ |
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81 |
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