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Omar Coello, Moisés Coronel, Darío Carpio, Boris X. Vintimilla & Luis Chuquimarca |
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Enhancing Apple’s Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging |
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2024 |
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14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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no |
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cidis @ cidis @ |
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244 |
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Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin |
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Title |
Classifying Healthy and Defective Fruits with a Multi-Input Architecture and CNN Models |
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2024 |
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14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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cidis @ cidis @ |
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245 |
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Emmanuel F. Morán, Boris X. Vintimilla, Miguel A. Realpe |
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Title |
Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves |
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2024 |
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 26th Iberoamerican Congress on Pattern Recognition, CIARP 2023 Coimbra 27 – 30 November 2023 |
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Vol. 14470 |
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257–271 |
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03029743 |
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978-303149017-0 |
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cidis @ cidis @ |
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249 |
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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 |
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Thermal Image Super-Resolution Challenge – PBVS 2020 |
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2020 |
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The 16th IEEE Workshop on Perception Beyond the Visible Spectrum on the Conference on Computer Vision and Pattern Recongnition (CVPR 2020) |
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2020-June |
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9151059 |
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432-439 |
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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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English |
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21607508 |
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978-172819360-1 |
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cidis @ cidis @ |
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123 |
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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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2023 |
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19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition (CVPR 2023) Vancouver, 18-28 junio 2023 |
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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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cidis @ cidis @ |
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210 |
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