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Author Dennis G. Romero; Roberto Yoncon; Angel Guale; Bonny Bayot; Fanny Panchana
Title Evaluación de técnicas de clasificación orientadas a la identificación automática de órganos del camarón a partir de imágenes histológicas Type Conference Article
Year 2017 Publication 15th LACCEI International Multi-Conference for Engineering, Education, and Technology Abbreviated Journal
Volume 2017-July Issue Pages (up) 1-6
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Notes Approved no
Call Number cidis @ cidis @ Serial 61
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Author Marjorie Chalen; Boris X. Vintimilla
Title Towards Action Prediction Applying Deep Learning Type Journal Article
Year 2019 Publication Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 Abbreviated Journal
Volume Issue Pages (up) pp. 1-3
Keywords action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm.
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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Call Number cidis @ cidis @ Serial 129
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Author Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa
Title PETRA: A Crowdsourcing-Based Platform for Rocks Data Collection and Characterization Type Conference Article
Year 2019 Publication IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador Abbreviated Journal
Volume Issue Pages (up) 1-6
Keywords
Abstract This paper presents details of a distributed platform intended for data acquisition, evaluation, storage and visualization, which is fully implemented under the crowdsourcing paradigm. The proposed platform is the result from collaboration between computer science and petrology researchers and it is intended for academic purposes. The platform is designed within a MTV (Model, Template and View) architecture and also designed for a collaborative data store and managing of rocks from multiple readers and writers, taking advantage of ubiquity of web applications, and neutrality of researchers from different

communities to validate the data. The platform is being used and validated by students and academics from our university; in the near future it will be open to other users interested on this topic.
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Notes Approved no
Call Number gtsi @ user @ Serial 112
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Author W. Agila; Gomer Rubio; L. Miranda; D. Sanaguano
Title Open Control Architecture for the Characterization and Control of the PEM Fuel Cell Type Conference Article
Year 2019 Publication IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador Abbreviated Journal
Volume Issue Pages (up) 1-5
Keywords PEM fuel cell, Experimental System, Control Engineering.
Abstract Proton exchange membrane (PEM) fuel cells, are an efficient and clean source of electrical energy. The analysis of its operation requires experimental work, which allows measuring, modeling and optimizing PEM fuel cells electrical behavior under different operating conditions. Therefore, having an experimentation platform that allows to easily carry out its study and control is essential. This research presents the design and development of an open instrumental system that allows measuring, controlling and determining the operating parameters of a PEM fuel cell. As results, the polarization curves, voltage-current, obtained by the system itself in different experimental conditions are shown. These curves are a very useful tool to evaluate the electrical behavior of the PEM battery.
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Notes Approved no
Call Number gtsi @ user @ Serial 118
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Author Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa
Title Fast CNN Stereo Depth Estimation through Embedded GPU Devices Type Journal Article
Year 2020 Publication Sensors 2020 Abbreviated Journal
Volume Vol. 2020-June Issue 11 Pages (up) pp. 1-13
Keywords stereo matching; deep learning; embedded GPU
Abstract Current CNN-based stereo depth estimation models can barely run under real-time

constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art

evaluations usually do not consider model optimization techniques, being that it is unknown what is

the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models

on three different embedded GPU devices, with and without optimization methods, presenting

performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth

estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture

for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically

augmenting the runtime speed of current models. In our experiments, we achieve real-time inference

speed, in the range of 5–32 ms, for 1216  368 input stereo images on the Jetson TX2, Jetson Xavier,

and Jetson Nano embedded devices.
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Publisher Place of Publication Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 14248220 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number cidis @ cidis @ Serial 132
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Author Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez
Title SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. Type Journal Article
Year 2020 Publication Abbreviated Journal In Sensors
Volume Vol. 2020-August Issue 16 Pages (up) pp. 1-23
Keywords object detection; urban outdoor panels; one-stage detectors; Single Shot MultiBox Detector (SSD); You Only Look Once (YOLO); detection metrics; object and scene imaging variabilities
Abstract This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO)

deep neural networks for the outdoor advertisement panel detection problem by handling multiple

and combined variabilities in the scenes. Publicity panel detection in images o ers important

advantages both in the real world as well as in the virtual one. For example, applications like Google

Street View can be used for Internet publicity and when detecting these ads panels in images, it could

be possible to replace the publicity appearing inside the panels by another from a funding company.

In our experiments, both SSD and YOLO detectors have produced acceptable results under variable

sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex

background and multiple panels in scenes. Due to the diculty of finding annotated images for the

considered problem, we created our own dataset for conducting the experiments. The major strength

of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable

when the publicity contained inside the panel is analyzed after detecting them. On the other side,

YOLO produced better panel localization results detecting a higher number of True Positive (TP)

panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models

with di erent types of semantic segmentation networks and using the same evaluation metrics is

also included.
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Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 14248220 Medium
Area Expedition Conference
Notes Approved no
Call Number cidis @ cidis @ Serial 133
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Author Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza
Title Open innovation at university: a systematic literature review Type Journal Article
Year 2020 Publication Advances in Intelligent Systems and Computing Abbreviated Journal
Volume 1159 AISC, 2020 Issue Pages (up) 3-14
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Notes Approved no
Call Number cidis @ cidis @ Serial 189
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Author Suárez P.
Title Processing and Representation of Multispectral Images Using Deep Learning Techniques Type Magazine Article
Year 2021 Publication In Electronic Letters on Computer Vision and Image Analysis Abbreviated Journal
Volume Vol. 19 Issue Issue 2 Pages (up) pp. 5-8
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Corporate Author Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector Thesis Master's thesis
Publisher Place of Publication Editor
Language Español Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes Approved yes
Call Number cidis @ cidis @ Serial 122
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Author Morocho-Cayamcela, M.E.
Title Increasing the Segmentation Accuracy of Aerial Images with Dilated Spatial Pyramid Pooling Type Journal Article
Year 2020 Publication Electronic Letters on Computer Vision and Image Analysis (ELCVIA) Abbreviated Journal
Volume Vol. 19 Issue Issue 2 Pages (up) pp. 17-21
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Notes Approved no
Call Number cidis @ cidis @ Serial 140
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Author Viñán-Ludeña M.S., De Campos L.M., Roberto Jacome Galarza, & Sinche Freire, J.
Title Social media influence: a comprehensive review in general and in tourism domain Type Journal Article
Year 2020 Publication Smart Innovation, Systems and Technologies. Abbreviated Journal
Volume 171, 2020 Issue Pages (up) 25-35
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Publisher Place of Publication Editor
Language Summary Language Original Title
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Notes Approved no
Call Number cidis @ cidis @ Serial 190
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