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Author  |
Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | 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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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 121 | ||
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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 | 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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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 123 | ||
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| Author |
Rosero Vasquez Shendry | ||||
| Title | Facial recognition: traditional methods vs. methods based on deep learning. Advances in Intelligent Systems and Computing – Information Technology and Systems Proceedings of ICITS 2020. | Type | Journal Article | ||
| Year | 2020 | Publication | Abbreviated Journal | ||
| Volume | Issue | Pages | 615-625 | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 145 | ||
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| Author |
Viñán-Ludeña M.S., De Campos L.M., Roberto Jacome Galarza, & Sinche Freire, J. | ||||
| Title | Social media influence: a comprehensive review in general and in tourism domain | Type | Journal Article | ||
| Year | 2020 | Publication | Smart Innovation, Systems and Technologies. | Abbreviated Journal | |
| Volume | 171, 2020 | Issue | Pages | 25-35 | |
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| Call Number | cidis @ cidis @ | Serial | 190 | ||
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| Author |
Viñán-Ludeña, M.S., Roberto Jacome Galarza, Montoya, L.R., Leon, A.V., & Ramírez, C.C. | ||||
| Title | Smart university: an architecture proposal for information management using open data for research projects. | Type | Journal Article | ||
| Year | 2020 | Publication | Advances in Intelligent Systems and Computing | Abbreviated Journal | |
| Volume | 1137 AISC, 2020 | Issue | Pages | 172-178 | |
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| Call Number | cidis @ cidis @ | Serial | 188 | ||
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| Author |
Xavier Soria; Edgar Riba; Angel D. Sappa | ||||
| Title | Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection | Type | Conference Article | ||
| Year | 2020 | Publication | 2020 IEEE Winter Conference on Applications of Computer Vision (WACV) | Abbreviated Journal | |
| Volume | Issue | 9093290 | Pages | 1912-1921 | |
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| Abstract | This paper proposes a Deep Learning based edge de- tector, which is inspired on both HED (Holistically-Nested Edge Detection) and Xception networks. The proposed ap- proach generates thin edge-maps that are plausible for hu- man eyes; it can be used in any edge detection task without previous training or fine tuning process. As a second contri- bution, a large dataset with carefully annotated edges, has been generated. This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons. Quantitative and qualitative evaluations have been performed on different benchmarks showing im- provements with the proposed method when F-measure of ODS and OIS are considered. | ||||
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| ISSN | ISBN | 978-172816553-0 | Medium | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 126 | ||
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