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Author Nayeth I. Solorzano Alcivar, Robert Loor, Stalyn Gonzabay Yagual, & Boris X. Vintimilla pdf  openurl
  Title Statistical Representations of a Dashboard to Monitor Educational Videogames in Natural Language Type Conference Article
  Year 2020 Publication ETLTC – ACM Chapter: International Conference on Educational Technology, Language and Technical Communication; Fukushima, Japan, 27-31 Enero 2020 Abbreviated Journal  
  Volume 77 Issue Pages (up)  
  Keywords  
  Abstract This paper explains how Natural Language (NL) processing by computers, through smart

programs as a way of Machine Learning (ML), can represent large sets of quantitative data as written

statements. The study recognized the need to improve the implemented web platform using a

dashboard in which we collected a set of extensive data to measure assessment factors of using

children´s educational games. In this case, applying NL is a strategy to give assessments, build, and

display more precise written statements to enhance the understanding of children´s gaming behavior.

We propose the development of a new tool to assess the use of written explanations rather than a

statistical representation of feedback information for the comprehension of parents and teachers with

a lack of primary level knowledge in statistics. Applying fuzzy logic theory, we present verbatim

explanations of children´s behavior playing educational videogames as NL interpretation instead of

statistical representations. An educational series of digital game applications for mobile devices,

identified as MIDI (Spanish acronym of “Interactive Didactic Multimedia for Children”) linked to a

dashboard in the cloud, is evaluated using the dashboard metrics. MIDI games tested in local primary

schools helps to evaluate the results of using the proposed tool. The guiding results allow analyzing

the degrees of playability and usability factors obtained from the data produced when children play a

MIDI game. The results obtained are presented in a comprehensive guiding evaluation report

applying NL for parents and teachers. These guiding evaluations are useful to enhance children's

learning understanding related to the school curricula applied to ludic digital games.
 
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  Call Number cidis @ cidis @ Serial 131  
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Author Patricia L. Suarez pdf  openurl
  Title Procesamiento y representación de imágenes multiespectrales usando técnicas de aprendizaje profundo (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). Ph.D. thesis. Type Book Chapter
  Year 2020 Publication Ediciones FIEC-ESPOL. Abbreviated Journal  
  Volume Issue Pages (up)  
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  Abstract  
  Address  
  Corporate Author Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector. Thesis  
  Publisher Place of Publication Editor  
  Language Español Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 144  
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Author Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. pdf  openurl
  Title Camera pose estimation in multi-view environments:from virtual scenarios to the real world Type Journal Article
  Year 2021 Publication In Image and Vision Computing Journal. (Article number 104182) Abbreviated Journal  
  Volume Vol. 110 Issue Pages (up)  
  Keywords Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments  
  Abstract This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired

images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of

overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly

trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the

relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity

on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the

scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used,

highlighting the importance on the similarity between virtual-real scenarios.
 
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  Language English Summary Language English Original Title  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 147  
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Author Jacome-Galarza L.-R pdf  openurl
  Title Crop yield prediction utilizing multimodal deep learning Type Conference Article
  Year 2021 Publication 16th Iberian Conference on Information Systems and Technologies, CISTI 2021, junio 23 – 26, 2021 Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords Agricultura de precisión; sensores remotos; aprendizaje profundo multimodal; IoT; agentes inteligentes; computación aplicada.  
  Abstract La agricultura de precisión es una práctica vital para

mejorar la producción de cosechas. El presente trabajo tiene

como objetivo desarrollar un modelo multimodal de aprendizaje

profundo que es capaz de producir un mapa de salud de

cosechas. El modelo recibe como entradas imágenes multiespectrales

y datos de sensores de campo (humedad,

temperatura, estado del suelo, etc.) y crea un mapa de

rendimiento de la cosecha. La utilización de datos multimodales

tiene como finalidad extraer patrones ocultos del estado de salud

de las cosechas y de esta manera obtener mejores resultados que

los obtenidos mediante los índices de vegetación.
 
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  Language Español Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 150  
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Author Rubio, G.A., Agila, W.E pdf  openurl
  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 (up)  
  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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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 153  
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Author Luis Jacome-Galarza, Monica Villavicencio-Cabezas, Miguel Realpe-Robalino, Jose Benavides-Maldonado pdf  openurl
  Title Software Engineering and Distributed Computing in image processing intelligent systems: a systematic literature review. Type Conference Article
  Year 2021 Publication 19th LACCEI International Multi-Conference for Engineering, Education, and Technology Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords processing, software engineering, deep learning, intelligent vision systems, cloud computing.  
  Abstract Deep learning is experiencing an upward technology trend that is revolutionizing intelligent systems in several domains, such as image and speech recognition, machine translation, social network filtering, and the like. By reviewing a total of 80 studies reported from 2016 to 2020, the present article evaluates the application of software engineering to the field

of intelligent image processing systems, it also offers insights about aspects related to distributed computing for this type of systems. Results indicate that several topics of software engineering are mostly applied when academics are involved in developing projects associated to this kind of intelligent systems. The findings provide evidences that Apache Spark is the most

utilized distributed computing framework for image processing. In addition, Tensorflow is a popular framework used to build convolutional neural networks, which are the prevailing deep learning algorithms used in intelligent image processing systems.

Also, among big cloud providers, Amazon Web Services is the preferred computing platform across the industry sectors, followed by Google cloud.
 
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  Call Number cidis @ cidis @ Serial 154  
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Author Rafael E. Rivadeneira, Angel Domingo Sappa, Vintimilla B. X. and Hammoud R. pdf  openurl
  Title A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. Type Journal Article
  Year 2022 Publication Sensors Abbreviated Journal Sensors  
  Volume Vol. 22 Issue Issue 6 Pages (up)  
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  Call Number cidis @ cidis @ Serial 170  
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Author Rafael E. Rivadeneira, Angel D. Sappa and Boris X. Vintimilla pdf  openurl
  Title Multi-Image Super-Resolution for Thermal Images. Type Conference Article
  Year 2022 Publication 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022), febrero 6-8 Abbreviated Journal  
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  Call Number cidis @ cidis @ Serial 181  
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Author Santos, V., Sappa, A.D., Oliveira, M. & de la Escalera, A. pdf  openurl
  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 (up)  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 158  
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Author Velesaca, H.O., Suárez, P. L., Mira, R., & Sappa, A.D. pdf  openurl
  Title Computer Vision based Food Grain Classification: a Comprehensive Survey Type Journal Article
  Year 2021 Publication In Computers and Electronics in Agriculture Journal. (Article number 106287) Abbreviated Journal  
  Volume Vol. 187 Issue Pages (up)  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 159  
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