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Author (down) 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 Type Conference Article
Year 2017 Publication 2017 International Conference on Deep Learning Technologies (ICDLT 2017) Abbreviated Journal
Volume Part F128535 Issue Pages 60-65
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Call Number cidis @ cidis @ Serial 56
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Author (down) Shendry Rosero Vásquez
Title Reconocimiento facial: técnicas tradicionales y técnicas de aprendizaje profundo, un análisis. (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). M.Sc. thesis Type Book Chapter
Year 2019 Publication Ediciones FIEC-ESPOL Abbreviated Journal
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Corporate Author Ph.D. Angel Sappa, Director de tesis & Ph.D. Boris Vintimilla, Codirector Thesis Master's thesis
Publisher Place of Publication Editor
Language Español Summary Language Original Title
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Notes Approved yes
Call Number gtsi @ user @ Serial 114
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Author (down) Sebastián Fuenzalida; Keyla Toapanta; Jonathan S. Paillacho Corredores; Dennys Paillacho
Title Forward and Inverse Kinematics of a Humanoid Robot Head for Social Human Robot-Interaction Type Conference Article
Year 2019 Publication IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador Abbreviated Journal
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Abstract This paper presents an analysis of forward and inverse kinematics for a humanoid robotic head. The robotic head is used for the study of social human-robot interaction, such as a support tool to maintain the attention of patients with Autism Spectrum Disorder. The design of a parallel robot that emulates human head movements through a closed structure is presented. The position and orientation in this space is controlled by three servomotors. For this, the solutions made for the kinematic problem are encompassed by a geometric analysis of a mobile base. This article describes a non-systematic method,

called the geometric method, and compares some of the most popular existing methods considering reliability and computational cost. The geometric method avoids the use of changing reference systems, and instead uses geometric

relationships to directly obtain the position based on joint variables; and the other way around. Therefore, it converges in a few iterations and has a low computational cost.
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Call Number gtsi @ user @ Serial 113
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Author (down) Sara Nieto, Evelyn Mejia, Ricardo Villacis, Fernanda Calderon, Hector Villegas, Jonathan Paillacho and Miguel Realpe
Title A Practical Study on Banana (Musa spp.) Plant Counting and Coverage Percentage Using Remote Sensing and Deep Learning Type Conference Article
Year 2023 Publication International Conference on Geospatial Information Sciences, iGISc 2023 Abbreviated Journal
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Call Number cidis @ cidis @ Serial 228
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Author (down) Santos, V., Sappa, A.D., Oliveira, M. & de la Escalera, A.
Title Editorial: Special Issue on Autonomous Driving and Driver Assistance Systems – Some Main Trends Type Journal Article
Year 2021 Publication In Journal: Robotics and Autonomous Systems. (Article number 103832) Abbreviated Journal
Volume Vol. 144 Issue Pages
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Call Number cidis @ cidis @ Serial 158
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Author (down) Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A.
Title Special Issue on Autonomous Driving and Driver Assistance Systems Type Journal Article
Year 2019 Publication In Robotics and Autonomous Systems Abbreviated Journal
Volume 121 Issue Pages
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Call Number gtsi @ user @ Serial 119
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Author (down) Rubio, G.A., Agila, W.E
Title A fuzzy model to manage water in polymer electrolyte membrane fuel cells Type Journal Article
Year 2021 Publication In Processes Journal. (Article number 904) Abbreviated Journal
Volume Vol. 9 Issue Issue 6 Pages
Keywords PEM fuel cell, fuzzy, neural network, electrical response, flooding, drying.
Abstract In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response and consequently, its autonomous operation. By applying load, current and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 mV to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 mV to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits.
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Language English Summary Language Original Title
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Call Number cidis @ cidis @ Serial 153
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Author (down) Rubio Abel; Agila Wilton; González Leandro; Aviles Jonathan
Title A Numerical Model for the Transport of Reactants in Proton Exchange Fuel Cells Type Conference Article
Year 2023 Publication 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 Oshawa 29 August – 1 September 2023 Abbreviated Journal
Volume Issue Pages 273 - 278
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ISSN ISBN 979-835033793-8 Medium
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Call Number cidis @ cidis @ Serial 230
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Author (down) Rosero Vasquez Shendry
Title Facial recognition: traditional methods vs. methods based on deep learning. Advances in Intelligent Systems and Computing – Information Technology and Systems Proceedings of ICITS 2020. Type Journal Article
Year 2020 Publication Abbreviated Journal
Volume Issue Pages 615-625
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Call Number cidis @ cidis @ Serial 145
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Author (down) Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco
Title Computer vision for image understanding. A comprehensive review Type Conference Article
Year 2019 Publication International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador Abbreviated Journal
Volume Issue Pages 248-259
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Abstract Computer Vision has its own Turing test: Can a machine describe the contents of an image or a video in the way a human being would do? In this paper, the progress of Deep Learning for image recognition is analyzed in order to know the answer to this question. In recent years, Deep Learning has increased considerably the precision rate of many tasks related to computer vision. Many datasets of labeled images are now available online, which leads to pre-trained models for many computer vision applications. In this work, we gather information of the latest techniques to perform image understanding and description. As a conclusion we obtained that the combination of Natural Language Processing (using Recurrent Neural Networks and Long Short-Term Memory) plus Image Understanding (using Convolutional Neural Networks) could bring new types of powerful and useful applications in which the computer will be able to answer questions about the content of images and videos. In order to build datasets of labeled images, we need a lot of work and most of the datasets are built using crowd work. These new applications have the potential to increase the human machine interaction to new levels of usability and user’s satisfaction.
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Call Number gtsi @ user @ Serial 97
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