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Author Rafael E. Rivadeneira; Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla.
Title (down) Thermal Image SuperResolution through Deep Convolutional Neural Network. Type Conference Article
Year 2019 Publication 16th International Conference on Image Analysis and Recognition (ICIAR 2019); Waterloo, Canadá Abbreviated Journal
Volume Issue Pages 417-426
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Abstract Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a superesolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process a new thermal images dataset is used. Di?erent experiments have been carried out, ?rstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www.cidis.espol.edu.ec/es/dataset
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Call Number gtsi @ user @ Serial 103
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Author Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X.
Title (down) Thermal Image Super-Resolution: A Novel Unsupervised Approach. Type Book Chapter
Year 2022 Publication Communications in Computer and Information Science, 15th International Communications in Computer and Information Science Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Abbreviated Journal BOOK
Volume 1474 Issue Pages 495-506
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Call Number cidis @ cidis @ Serial 179
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Author Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla
Title (down) Thermal Image Super-Resolution: a Novel Architecture and Dataset Type Conference Article
Year 2020 Publication The 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020); Valletta, Malta; 27-29 Febrero 2020 Abbreviated Journal
Volume 4 Issue Pages 111-119
Keywords Thermal images, Far Infrared, Dataset, Super-Resolution.
Abstract This paper proposes a novel CycleGAN architecture for thermal image super-resolution, together with a large

dataset consisting of thermal images at different resolutions. The dataset has been acquired using three thermal

cameras at different resolutions, which acquire images from the same scenario at the same time. The thermal

cameras are mounted in rig trying to minimize the baseline distance to make easier the registration problem.

The proposed architecture is based on ResNet6 as a Generator and PatchGAN as Discriminator. The novelty

on the proposed unsupervised super-resolution training (CycleGAN) is possible due to the existence of aforementioned thermal images—images of the same scenario with different resolutions. The proposed approach

is evaluated in the dataset and compared with classical bicubic interpolation. The dataset and the network are

available.
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ISSN ISBN 978-989758402-2 Medium
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Call Number gtsi @ user @ Serial 121
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Author Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al.
Title (down) Thermal Image Super-Resolution Challenge Results- PBVS 2022. Type Conference Article
Year 2022 Publication Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE
Volume 2022-June Issue Pages 349-357
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Abstract 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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Call Number cidis @ cidis @ Serial 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
Title (down) Thermal Image Super-Resolution Challenge Results – PBVS 2023 Type Conference Article
Year 2023 Publication 19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition CVPR 2023, junio 18-28 Abbreviated Journal
Volume 2023-June Issue Pages 470 - 478
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ISSN 21607508 ISBN 979-835030249-3 Medium
Area Expedition Conference
Notes Approved no
Call Number cidis @ cidis @ Serial 210
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Author Rivadeneira R.E., Sappa A.D., Vintimilla B.X., Nathan S., Kansal P., Mehri A et al.
Title (down) Thermal Image Super-Resolution Challenge – PBVS 2021. Type Conference Article
Year 2021 Publication In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021., junio 19 – 25, 2021 Abbreviated Journal
Volume Issue Pages 4354-4362
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Call Number cidis @ cidis @ Serial 151
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Author Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla; Lin Guo; Jiankun Hou; Armin Mehri; Parichehr Behjati; Ardakani Heena Patel; Vishal Chudasama; Kalpesh Prajapati; Kishor P. Upla; Raghavendra Ramachandra; Kiran Raja; Christoph Busch; Feras Almasri; Olivier Debeir; Sabari Nathan; Priya Kansal; Nolan Gutierrez; Bardia Mojra; William J. Beksi
Title (down) Thermal Image Super-Resolution Challenge – PBVS 2020 Type Conference Article
Year 2020 Publication The 16th IEEE Workshop on Perception Beyond the Visible Spectrum on the Conference on Computer Vision and Pattern Recongnition (CVPR 2020) Abbreviated Journal
Volume 2020-June Issue 9151059 Pages 432-439
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Abstract This paper summarizes the top contributions to the first challenge on thermal image super-resolution (TISR) which was organized as part of the Perception Beyond the Visible Spectrum (PBVS) 2020 workshop. In this challenge, a novel thermal image dataset is considered together with stateof-the-art approaches evaluated under a common framework.

The dataset used in the challenge consists of 1021 thermal images, obtained from three distinct thermal cameras at different resolutions (low-resolution, mid-resolution, and high-resolution), resulting in a total of 3063 thermal images. From each resolution, 951 images are used for training and 50 for testing while the 20 remaining images are used for two proposed evaluations. The first evaluation consists of downsampling the low-resolution, midresolution, and high-resolution thermal images by x2, x3 and x4 respectively, and comparing their super-resolution

results with the corresponding ground truth images. The second evaluation is comprised of obtaining the x2 superresolution from a given mid-resolution thermal image and comparing it with the corresponding semi-registered highresolution thermal image. Out of 51 registered participants, 6 teams reached the final validation phase.
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Language English Summary Language Original Title
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ISSN 21607508 ISBN 978-172819360-1 Medium
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Call Number cidis @ cidis @ Serial 123
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Author Henry O. Velesaca, Patricia L. Suarez, Dario Carpio, and Angel D. Sappa
Title (down) Synthesized Image Datasets: Towards an Annotation-Free Instance Segmentation Strategy Type Conference Article
Year 2021 Publication 16 International Symposium on Visual Computing. Octubre 4-6, 2021. Lecture Notes in Computer Science Abbreviated Journal
Volume 13017 Issue Pages 131-143
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Call Number cidis @ cidis @ Serial 163
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Author G.A. Rubio; Wilton Agila
Title (down) Sustainable Energy: A Strategic View of Fuel Cells Type Conference Article
Year 2019 Publication 8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania Abbreviated Journal
Volume Issue Pages 239-243
Keywords
Abstract Based on the model of the proton exchange fuel cell in a strategic context,

this document develops the issue of energy as one of the pillars to achieve the

sustainability of our planet, considering the future scenarios up to the year 2060 of the

situation energy, hydrogen as a strategic vector and the contribution of the fuel cell in

solving the serious problems of environmental pollution and economic inequity that

humanity faces; for its application in the energy generation, telecommunications and

vehicle manufacturing industries.
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Call Number gtsi @ user @ Serial 110
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Author Nayeth I. Solorzano Alcivar, Robert Loor, Stalyn Gonzabay Yagual, & Boris X. Vintimilla
Title (down) Statistical Representations of a Dashboard to Monitor Educational Videogames in Natural Language Type Conference Article
Year 2020 Publication ETLTC – ACM Chapter: International Conference on Educational Technology, Language and Technical Communication; Fukushima, Japan, 27-31 Enero 2020 Abbreviated Journal
Volume 77 Issue Pages
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Abstract This paper explains how Natural Language (NL) processing by computers, through smart

programs as a way of Machine Learning (ML), can represent large sets of quantitative data as written

statements. The study recognized the need to improve the implemented web platform using a

dashboard in which we collected a set of extensive data to measure assessment factors of using

children´s educational games. In this case, applying NL is a strategy to give assessments, build, and

display more precise written statements to enhance the understanding of children´s gaming behavior.

We propose the development of a new tool to assess the use of written explanations rather than a

statistical representation of feedback information for the comprehension of parents and teachers with

a lack of primary level knowledge in statistics. Applying fuzzy logic theory, we present verbatim

explanations of children´s behavior playing educational videogames as NL interpretation instead of

statistical representations. An educational series of digital game applications for mobile devices,

identified as MIDI (Spanish acronym of “Interactive Didactic Multimedia for Children”) linked to a

dashboard in the cloud, is evaluated using the dashboard metrics. MIDI games tested in local primary

schools helps to evaluate the results of using the proposed tool. The guiding results allow analyzing

the degrees of playability and usability factors obtained from the data produced when children play a

MIDI game. The results obtained are presented in a comprehensive guiding evaluation report

applying NL for parents and teachers. These guiding evaluations are useful to enhance children's

learning understanding related to the school curricula applied to ludic digital games.
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Call Number cidis @ cidis @ Serial 131
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