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Author |
Luis C. Herrera, Leslie del R. Lima, Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. |
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Title |
Metrics Design of Usability and Behavior Analysis of a Human-Robot-Game Platform. |
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Conference Article |
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Year |
2021 |
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The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communication in Computer and Information Science |
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1388 |
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164-178 |
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Call Number |
cidis @ cidis @ |
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191 |
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Author |
Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X. |
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Title |
Thermal Image Super-Resolution: A Novel Unsupervised Approach. |
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Book Chapter |
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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 |
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BOOK |
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1474 |
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495-506 |
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cidis @ cidis @ |
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179 |
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Author |
Velez R., Paredes A., Silva S., Paillacho D., and Paillacho J. |
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Title |
Implementation of a UVC lights disinfection system for a diferential robot applying security methods in indoor. |
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Conference Article |
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Year |
2022 |
Publication |
Communications in Computer and Information Science, International Conference on Applied Technologies (ICAT 2021), octubre 27-29 |
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CONFERENCE |
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1535 |
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319-331 |
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cidis @ cidis @ |
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178 |
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Author |
Roberto Jacome Galarza. |
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Title |
Multimodal deep learning for crop yield prediction. |
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Conference Article |
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2022 |
Publication |
Doctoral Symposium on Information and Communication Technologies –DSICT 2022. Octubre 12-14. |
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1647 |
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Communicationsin Computer and Infor |
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106-117 |
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cidis @ cidis @ |
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193 |
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Author |
Dennys Paillacho, Nayeth Solórzano, Michael Arce, María Plues & Edwin Eras |
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Title |
Advanced metrics to evaluate autistic children's attention and emotions from facial characteristics using a human robot-game interface |
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Conference Article |
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Year |
2023 |
Publication |
Communications in Computer and Information Science. 11th Conferencia Ecuatoriana de Tecnologías de la Información y Comunicación TICEC 2023 |
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1885 CCIS |
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234 - 247 |
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18650929 |
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978-303145437-0 |
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cidis @ cidis @ |
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221 |
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Author |
Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho |
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Title |
Development of animated facial expression to express emotions in a robot: RobotIcon. |
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Conference Article |
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Year |
2017 |
Publication |
IEEE Ecuador Technical Chapter Meeting (ETCM) |
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2017-January |
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1-6 |
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gtsi @ user @ |
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71 |
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Author |
Dennis G. Romero; Roberto Yoncon; Angel Guale; Bonny Bayot; Fanny Panchana |
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Title |
Evaluación de técnicas de clasificación orientadas a la identificación automática de órganos del camarón a partir de imágenes histológicas |
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Conference Article |
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Year |
2017 |
Publication |
15th LACCEI International Multi-Conference for Engineering, Education, and Technology |
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2017-July |
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1-6 |
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cidis @ cidis @ |
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61 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Infrared Image Colorization based on a Triplet DCGAN Architecture. |
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Conference Article |
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Year |
2017 |
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13th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2017. (This paper has been selected as “Best Paper Award” ) |
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2017-July |
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212-217 |
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cidis @ cidis @ |
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62 |
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Author |
José Reyes; Axel Godoy; Miguel Realpe. |
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Title |
Uso de software de código abierto para fusión de imágenes agrícolas multiespectrales adquiridas con drones. |
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Conference Article |
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2019 |
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International Multi-Conference of Engineering, Education and Technology (LACCEI 2019); Montego Bay, Jamaica |
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2019-July |
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Los drones o aeronaves no tripuladas son muy útiles para la adquisición de imágenes, de forma mucho más simple que los satélites o aviones. Sin embargo, las imágenes adquiridas por drones deben ser combinadas de alguna forma para convertirse en información de valor sobre un terreno o cultivo. Existen diferentes programas que reciben imágenes y las combinan en una sola imagen, cada uno con diferentes características (rendimiento, precisión, resultados, precio, etc.). En este estudio se revisaron diferentes programas de código abierto para fusión de imágenes, con el ?n de establecer cuál de ellos es más útil, especí?camente para ser utilizado por pequeños y medianos agricultores en Ecuador. Los resultados pueden ser de interés para diseñadores de software, ya que al utilizar código abierto, es posible modi?car e integrar los programas en un ?ujo de trabajo más simpli?cado. Además, que permite disminuir costos debido a que no requiere de pagos de licencias para su uso, lo cual puede repercutir en un mayor acceso a la tecnología para los pequeños y medianos agricultores. Como parte de los resultados de este estudio se ha creado un repositorio de acceso público con algoritmos de pre-procesamiento necesarios para manipular las imágenes adquiridas por una cámara multiespectral y para luego obtener un mapa completo en formatos RGB, CIR y NDVI. |
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gtsi @ user @ |
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102 |
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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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Title |
Thermal Image Super-Resolution Challenge – PBVS 2020 |
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Conference Article |
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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 @ |
Serial |
123 |
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