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Author |
Pereira J., Mora M. & W. Agila |
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Title |
Qualitative Model to Maximize Shrimp Growth at Low Cost |
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2021 |
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5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 |
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cidis @ cidis @ |
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167 |
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Author |
Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. |
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Title |
LDC: Lightweight Dense CNN for Edge Detection. |
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Journal Article |
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2022 |
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IEEE Access journal |
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Vol. 10 |
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pp. 68281-68290 |
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yes |
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cidis @ cidis @ |
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183 |
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Author |
Ulises Gildardo Quiroz Antúnez, Alejandro Ismael Monterroso Rivas, María Fernanda Calderón Vega, Adán Guillermo Ramírez García |
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Title |
APTITUDE OF COFFEE (COFFEA ARABICA L.) AND CACAO (THEOBROMA CACAO L.) CROPS CONSIDERING CLIMATE CHANGE |
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Journal Article |
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Year |
2022 |
Publication |
Granja |
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Vol. 36 |
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Issue 2 |
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cidis @ cidis @ |
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200 |
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Author |
Armin Mehri; Parichehr Behjati; Angel Domingo Sappa |
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Title |
TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution. |
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Journal Article |
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2023 |
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IEEE Access |
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Vol. 11 |
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pp. 11529-11540 |
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no |
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cidis @ cidis @ |
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207 |
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Author |
Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia |
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Journal Article |
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Year |
2023 |
Publication |
Dense extreme inception network for edge detection. Pattern Recognition |
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Vol. 139 |
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no |
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cidis @ cidis @ |
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216 |
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Author |
Abel Rubio, Wilton Agila, Leandro González & Jonathan Aviles-Cedeno |
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Title |
Distributed Intelligence in Autonomous PEM Fuel Cell Control. |
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Journal Article |
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Year |
2023 |
Publication |
Energies 2023 |
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Vol. 16 |
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Issue 12 |
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no |
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cidis @ cidis @ |
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217 |
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Author |
Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa |
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Title |
Corn Kernel Classification From Few Training Samples |
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Journal Article |
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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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no |
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cidis @ cidis @ |
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223 |
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Author |
Marjorie Chalen; Boris X. Vintimilla |
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Title |
Towards Action Prediction Applying Deep Learning |
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Journal Article |
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Year |
2019 |
Publication |
Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 |
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pp. 1-3 |
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action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm. |
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Abstract |
Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task. |
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no |
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Call Number |
cidis @ cidis @ |
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129 |
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Author |
Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa |
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Title |
Feature Point Descriptors: Infrared and Visible Spectra |
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Journal Article |
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Year |
2014 |
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Sensors Journal |
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Vol. 14 |
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pp. 3690-3701 |
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Keywords |
cross-spectral imaging; feature point descriptors |
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Abstract |
This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given. |
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English |
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English |
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no |
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Call Number |
cidis @ cidis @ |
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28 |
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Author |
Dennys Paillacho; F. Novillo; W. Agila.; V. Huilcapi |
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Title |
Impacto de las redes de comunicaciones en los Sistemas Robóticos de Control |
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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. 97-102 |
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Keywords |
Ethernet, CAN, Swichted Ethernet, Sistemas de control en red, Ciclo de comunicación, Control de ajuste de trayectoria |
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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 @ |
Serial |
33 |
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