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Author Michael Teutsch, Angel Sappa & Riad Hammoud url  openurl
  Title Computer Vision in the Infrared Spectrum: Challenges and ApproachesComputer Vision in the Infrared Spectrum: Challenges and Approaches Type Journal Article
  Year (down) 2021 Publication Synthesis Lectures on Computer Vision Abbreviated Journal  
  Volume Vol. 10 No. 2 Issue Pages pp. 138  
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  Call Number cidis @ cidis @ Serial 166  
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Author Pereira J., Mora M. & W. Agila url  openurl
  Title Qualitative Model to Maximize Shrimp Growth at Low Cost Type Journal Article
  Year (down) 2021 Publication 5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 Abbreviated Journal  
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  Call Number cidis @ cidis @ Serial 167  
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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 (down) 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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  Call Number cidis @ cidis @ Serial 153  
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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 (down) 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 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 (down) 2021 Publication In Computers and Electronics in Agriculture Journal. (Article number 106287) Abbreviated Journal  
  Volume Vol. 187 Issue Pages  
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  Call Number cidis @ cidis @ Serial 159  
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Author Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez pdf  isbn
openurl 
  Title SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. Type Journal Article
  Year (down) 2020 Publication Abbreviated Journal In Sensors  
  Volume Vol. 2020-August Issue 16 Pages 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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  ISSN ISBN 14248220 Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 133  
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Author Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa pdf  openurl
  Title Fast CNN Stereo Depth Estimation through Embedded GPU Devices Type Journal Article
  Year (down) 2020 Publication Sensors 2020 Abbreviated Journal  
  Volume Vol. 2020-June Issue 11 Pages 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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  ISSN 14248220 ISBN Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 132  
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Author Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza url  openurl
  Title Open innovation at university: a systematic literature review Type Journal Article
  Year (down) 2020 Publication Advances in Intelligent Systems and Computing Abbreviated Journal  
  Volume 1159 AISC, 2020 Issue Pages 3-14  
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  Call Number cidis @ cidis @ Serial 189  
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Author Morocho-Cayamcela, M.E. pdf  openurl
  Title Increasing the Segmentation Accuracy of Aerial Images with Dilated Spatial Pyramid Pooling Type Journal Article
  Year (down) 2020 Publication Electronic Letters on Computer Vision and Image Analysis (ELCVIA) Abbreviated Journal  
  Volume Vol. 19 Issue Issue 2 Pages pp. 17-21  
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  Call Number cidis @ cidis @ Serial 140  
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Author Morocho-Cayamcela, M.E. & W. Lim pdf  openurl
  Title Lateral confinement of high-impedance surface-waves through reinforcement learning Type Journal Article
  Year (down) 2020 Publication Electronics Letters Abbreviated Journal  
  Volume Vol. 56 Issue 23, 12 November 2020 Pages pp. 1262-1264  
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  Abstract The authors present a model-free policy-based reinforcement learning

model that introduces perturbations on the pattern of a metasurface.

The objective is to learn a policy that changes the size of the

patches, and therefore the impedance in the sides of an artificially structured

material. The proposed iterative model assigns the highest reward

when the patch sizes allow the transmission along a constrained path

and penalties when the patch sizes make the surface wave radiate to

the sides of the metamaterial. After convergence, the proposed

model learns an optimal patch pattern that achieves lateral confinement

along the metasurface. Simulation results show that the proposed

learned-pattern can effectively guide the electromagnetic wave

through a metasurface, maintaining its instantaneous eigenstate when

the homogeneity is perturbed. Moreover, the pattern learned to

prevent reflections by changing the patch sizes adiabatically. The

reflection coefficient S1, 2 shows that most of the power gets transferred

from the source to the destination with the proposed design.		  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 139  
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