| Records |
Author  |
Rivadeneira R.E., Sappa A.D., Vintimilla B.X., Nathan S., Kansal P., Mehri A et al. |
| Title |
Thermal Image Super-Resolution Challenge – PBVS 2021. |
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Conference Article |
| Year |
2021 |
Publication |
In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021., junio 19 – 25, 2021 |
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4354-4362 |
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no |
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cidis @ cidis @ |
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151 |
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| Author |
Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X. |
| Title |
Thermal Image Super-Resolution: A Novel Unsupervised Approach. |
Type |
Book Chapter |
| Year |
2022 |
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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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no |
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cidis @ cidis @ |
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179 |
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| Author |
Roberto Jacome Galarza. |
| Title |
Multimodal deep learning for crop yield prediction. |
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Conference Article |
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2022 |
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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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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 |
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Conference Article |
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2019 |
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International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador |
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248-259 |
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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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no |
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gtsi @ user @ |
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97 |
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| Author |
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. |
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Journal Article |
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2020 |
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615-625 |
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no |
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cidis @ cidis @ |
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145 |
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| Author |
Rubio Abel; Agila Wilton; González Leandro; Aviles Jonathan |
| Title |
A Numerical Model for the Transport of Reactants in Proton Exchange Fuel Cells |
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Conference Article |
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2023 |
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12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 Oshawa 29 August – 1 September 2023 |
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273 - 278 |
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979-835033793-8 |
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no |
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cidis @ cidis @ |
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230 |
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| Author |
Rubio, G.A., Agila, W.E |
| Title |
A fuzzy model to manage water in polymer electrolyte membrane fuel cells |
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Journal Article |
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2021 |
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In Processes Journal. (Article number 904) |
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Vol. 9 |
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Issue 6 |
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PEM fuel cell, fuzzy, neural network, electrical response, flooding, drying. |
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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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English |
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cidis @ cidis @ |
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153 |
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| Author |
Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A. |
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Special Issue on Autonomous Driving and Driver Assistance Systems |
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Journal Article |
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2019 |
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In Robotics and Autonomous Systems |
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121 |
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gtsi @ user @ |
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119 |
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Santos, V., Sappa, A.D., Oliveira, M. & de la Escalera, A. |
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Editorial: Special Issue on Autonomous Driving and Driver Assistance Systems – Some Main Trends |
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Journal Article |
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2021 |
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In Journal: Robotics and Autonomous Systems. (Article number 103832) |
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Vol. 144 |
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cidis @ cidis @ |
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158 |
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Sara Nieto, Evelyn Mejia, Ricardo Villacis, Fernanda Calderon, Hector Villegas, Jonathan Paillacho and Miguel Realpe |
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A Practical Study on Banana (Musa spp.) Plant Counting and Coverage Percentage Using Remote Sensing and Deep Learning |
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Conference Article |
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2024 |
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Lecture Notes in Geoinformation and Cartography: 3rd International Conference on Geospatial Information Sciences, iGISc 2023 Ciudad de México 14-17 November 2023 |
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147 - 158 |
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cidis @ cidis @ |
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228 |
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