| Records |
| Author |
Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla |
Title  |
Deep learning-based vegetation index estimation |
Type |
Book Chapter |
| Year |
2021 |
Publication |
Generative Adversarial Networks for Image-to-Image Translation Book. |
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Chapter 9 |
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Issue 2 |
Pages |
205-232 |
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no |
| Call Number |
cidis @ cidis @ |
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137 |
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| Author |
Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia |
| Title |
Dense extreme inception network for edge detection. |
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Journal Article |
| Year |
2023 |
Publication |
Pattern Recognition |
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Vol. 139 |
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00313203 |
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no |
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cidis @ cidis @ |
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216 |
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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 |
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Conference Article |
| Year |
2020 |
Publication |
2020 IEEE Winter Conference on Applications of Computer Vision (WACV) |
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9093290 |
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1912-1921 |
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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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978-172816553-0 |
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no |
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cidis @ cidis @ |
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126 |
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| Author |
Patricia L. Suarez, Dario Carpio, Angel Sappa |
| Title |
Depth Map Estimation from a Single 2D Image |
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Conference Article |
| Year |
2023 |
Publication |
17th International Conference On Signal Image Technology & Internet Based Systems, Bangkok, 8-10 November 2023 |
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347-353 |
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no |
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cidis @ cidis @ |
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226 |
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| Author |
Patricia Suarez, Angel Sappa |
| Title |
Depth-Conditioned Thermal-like Image Generation |
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Conference Article |
| Year |
2024 |
Publication |
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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243 |
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| Author |
Alex Ferrin; Julio Larrea; Miguel Realpe; Daniel Ochoa |
| Title |
Detection of utility poles from noisy Point Cloud Data in Urban environments. |
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Conference Article |
| Year |
2018 |
Publication |
Artificial Intelligence and Cloud Computing Conference (AICCC 2018) |
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53-57 |
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In recent years 3D urban maps have become more common, thus providing complex point clouds that include diverse urban furniture such as pole-like objects. Utility poles detection in urban environment is of particular interest for electric utility companies in order to maintain an updated inventory for better planning and management. The present study develops an automatic method for the detection of utility poles from noisy point cloud data of Guayaquil – Ecuador, where many poles are located next to buildings, or houses are built until the border of the sidewalk getting very close to poles, which increases the difficulty of discriminating poles, walls, columns, fences and building corners. |
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gtsi @ user @ |
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94 |
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| Author |
Ortiz J.; Londono J.; Novillo F.; Ampuno A.; Chávez M. |
| Title |
Determinación de Invariantes en Grandes Centros de Datos basados en Topología Fat-Tree |
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Journal Article |
| Year |
2015 |
Publication |
Revista Politécnica |
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Vol. 35 |
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pp. 91-96 |
| Keywords |
Invariantes de red, topologías, Fat-tree, simulación, emulación |
| Abstract |
Durante los últimos años ha existido un fuerte incremento en el acceso a internet, causando que los centros de datos ( DC) deban adaptar dinámicamente su infraestructura de red de cara a enfrentar posibles problemas de congestión, la cual no siempre se da de forma oportuna. Ante esto, nuevas topologías de red se han propuesto en los últimos años, como una forma de brindar mejores condiciones para el manejo de tráfico interno, sin embargo es común que para el estudio de estas mejoras, se necesite recrear el comportamiento de un verdadero DC en modelos de simulación/emulación. Por lo tanto se vuelve esencial validar dichos modelos, de cara a obtener resultados coherentes con la realidad. Esta validación es posible por medio de la identificación de ciertas propiedades que se deducen a partir de las variables y los parámetros que describen la red, y que se mantienen en las topologías de los DC para diversos escenarios y/o configuraciones. Estas propiedades, conocidas como invariantes, son una expresión del funcionamiento de la red en ambientes reales, como por ejemplo la ruta más larga entre dos nodos o el número de enlaces mínimo que deben fallar antes de una pérdida de conectividad en alguno de los nodos de la red. En el presente trabajo se realiza la identificación, formulación y comprobación de dos invariantes para la topología Fat-Tree, utilizando como software emulador a mininet. Las conclusiones muestran resultados concordantes entre lo analítico y lo práctico. |
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Escuela Politécnica Nacional |
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Español |
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Español |
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no |
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cidis @ cidis @ |
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32 |
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| Author |
Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho |
| Title |
Development of animated facial expression to express emotions in a robot: RobotIcon. |
Type |
Conference Article |
| 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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no |
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gtsi @ user @ |
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71 |
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| Author |
Abel Rubio, Wilton Agila, Leandro González & Jonathan Aviles-Cedeno |
| Title |
Distributed Intelligence in Autonomous PEM Fuel Cell Control. |
Type |
Journal Article |
| Year |
2023 |
Publication |
Energies 2023 |
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Vol. 16 |
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Issue 12 |
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19961073 |
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no |
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cidis @ cidis @ |
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217 |
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| Author |
Angel D. Sappa, Patricia L. Suárez, Henry O. Velesaca, Darío Carpio |
| Title |
Domain adaptation in image dehazing: exploring the usage of images from virtual scenarios. |
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Conference Article |
| Year |
2022 |
Publication |
16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing (CGVCVIP 2022), julio 20-22 |
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85-92 |
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cidis @ cidis @ |
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182 |
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