| Records |
| Author |
Roberto Jacome Galarza. |
| Title |
Multimodal deep learning for crop yield prediction. |
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Conference Article |
| Year |
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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Henry O. Velesaca, Patricia L. Suárez, Dario Carpio, Rafael E. Rivadeneira, Ángel Sánchez, Angel D. Sappa. |
| Title |
Video Analytics in Urban Environments: Challenges and Approaches. |
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Book Chapter |
| Year |
2022 |
Publication |
ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series |
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BOOK |
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224 |
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101-122 |
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cidis @ cidis @ |
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196 |
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| Author |
Dennys Paillacho; F. Novillo; W. Agila.; V. Huilcapi |
| Title |
Impacto de las redes de comunicaciones en los Sistemas Robóticos de Control |
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Journal Article |
| Year |
2015 |
Publication |
Revista Politécnica |
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Vol. 35 |
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pp. 97-102 |
| Keywords |
Ethernet, CAN, Swichted Ethernet, Sistemas de control en red, Ciclo de comunicación, Control de ajuste de trayectoria |
| Abstract |
El análisis de incidencia que tienen las redes de comunicaciones sobre el comportamiento de los sistemas robóticos de control en red muestra grandes dificultades cuando se quieren hacer evaluaciones de tipo analítico. Por tal razón, en este trabajo un análisis que utiliza una aproximación basada en simulación es propuesto, de manera que el comportamiento temporal y espacial de un sistema robótico de control en red pueda ser evaluado. Para tal efecto, se propone un entorno de validación mediante el cual una red de comunicaciones permita distribuir mensajes de control entre el controlador principal y los controladores remotos ubicados en cada articulación angular del robot manipulador planar. Las interacciones entre los componentes del sistema han sido modeladas mediante un sistema de capas. Dicho modelo es llevado a un entorno de simulación con la finalidad de analizar el impacto de distintos parámetros de comunicaciones (i.e. tipo de red, tasa de datos y tamaño de datos) sobre el ciclo de comunicación y el error de seguimiento de trayectoria en un sistema robótico. |
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Escuela Politécnica Nacional |
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Español |
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Español |
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cidis @ cidis @ |
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33 |
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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 |
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2015 |
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Revista Politécnica |
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Vol. 35 |
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pp. 91-96 |
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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 |
Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa |
| Title |
Corn Kernel Classification From Few Training Samples |
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Journal Article |
| Year |
2023 |
Publication |
In journal Artificial Intelligence in Agriculture |
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Vol. 9 |
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pp. 89-99 |
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25897217 |
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no |
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cidis @ cidis @ |
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223 |
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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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no |
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cidis @ cidis @ |
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182 |
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| Author |
Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla, Henry O. Velesaca. |
| Title |
Human Body Pose Estimation in Multi-view Environments. |
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Book Chapter |
| Year |
2022 |
Publication |
ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series |
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BOOK |
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224 |
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79-99 |
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cidis @ cidis @ |
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197 |
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| Author |
Sianna Puente; Cindy Madrid; Miguel Realpe; Boris X. Vintimilla |
| Title |
An Empirical Comparison of DCNN libraries to implement the Vision Module of a Danger Management System |
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Conference Article |
| Year |
2017 |
Publication |
2017 International Conference on Deep Learning Technologies (ICDLT 2017) |
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Part F128535 |
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60-65 |
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cidis @ cidis @ |
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56 |
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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 |
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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 |
Patricia Suarez, Henry Velesaca, Dario Carpio, Angel Sappa, Patricia Urdiales, Francisca Burgos |
| Title |
Deep Learning based Shrimp Classification |
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Conference Article |
| Year |
2022 |
Publication |
17th International Symposium on Visual Computing, San Diego, USA, Octubre 3-5. Lecture Notes in Computer Science (LNCS) |
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13598 LNCS |
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36-45 |
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cidis @ cidis @ |
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194 |
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