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Author Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco pdf  openurl
  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  
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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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Author Marjorie Chalen; Boris X. Vintimilla pdf  openurl
  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  
  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 Armin Mehri; Angel D. Sappa pdf  openurl
  Title Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples Type Conference Article
  Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal  
  Volume Issue Pages pp 971-979  
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  Abstract This paper presents a novel approach for colorizing

near infrared (NIR) images. The approach is based on

image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored

networks that require less computation times, converge

faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation

metrics—and qualitatively evaluated showing considerable

improvements with respect to the state of the art
 
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  Call Number gtsi @ user @ Serial 105  
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud pdf  openurl
  Title Image Vegetation Index through a Cycle Generative Adversarial Network Type Conference Article
  Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal  
  Volume Issue Pages 1014-1021  
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  Abstract This paper proposes a novel approach to estimate the

Normalized Difference Vegetation Index (NDVI) just from

an RGB image. The NDVI values are obtained by using

images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The

cycled GAN network is able to obtain a NIR image from

a given gray scale image. It is trained by using unpaired

set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are

obtained from the provided RGB images). Then, the NIR

image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous

approaches are also provided.
 
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  Call Number gtsi @ user @ Serial 106  
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Author Angel Morera; Angel Sánchez; Angel D. Sappa; José F. Vélez pdf  openurl
  Title Robust Detection of Outdoor Urban Advertising Panels in Static Images. Type Conference Article
  Year 2019 Publication 17th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2019); Ávila, España. Communications in Computer and Information Science Abbreviated Journal  
  Volume 1047 Issue Pages 246-256  
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  Abstract One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising

panels. For such a purpose, a previous stage is to accurately detect and

locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based

on a deep neural network architecture that minimizes the number of

false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection

over Union (IoU) accuracy metric make this proposal applicable in real

complex urban images.
 
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  Call Number gtsi @ user @ Serial 107  
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Author José Reyes; Axel Godoy; Miguel Realpe. pdf  openurl
  Title Uso de software de código abierto para fusión de imágenes agrícolas multiespectrales adquiridas con drones. Type Conference Article
  Year 2019 Publication International Multi-Conference of Engineering, Education and Technology (LACCEI 2019); Montego Bay, Jamaica Abbreviated Journal  
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  Abstract Los drones o aeronaves no tripuladas son muy útiles para la adquisición de imágenes, de forma mucho más simple que los satélites o aviones. Sin embargo, las imágenes adquiridas por drones deben ser combinadas de alguna forma para convertirse en información de valor sobre un terreno o cultivo. Existen diferentes programas que reciben imágenes y las combinan en una sola imagen, cada uno con diferentes características (rendimiento, precisión, resultados, precio, etc.). En este estudio se revisaron diferentes programas de código abierto para fusión de imágenes, con el ?n de establecer cuál de ellos es más útil, especí?camente para ser utilizado por pequeños y medianos agricultores en Ecuador. Los resultados pueden ser de interés para diseñadores de software, ya que al utilizar código abierto, es posible modi?car e integrar los programas en un ?ujo de trabajo más simpli?cado. Además, que permite disminuir costos debido a que no requiere de pagos de licencias para su uso, lo cual puede repercutir en un mayor acceso a la tecnología para los pequeños y medianos agricultores. Como parte de los resultados de este estudio se ha creado un repositorio de acceso público con algoritmos de pre-procesamiento necesarios para manipular las imágenes adquiridas por una cámara multiespectral y para luego obtener un mapa completo en formatos RGB, CIR y NDVI.  
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  Call Number gtsi @ user @ Serial 102  
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Author Rafael E. Rivadeneira; Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla. pdf  openurl
  Title Thermal Image SuperResolution through Deep Convolutional Neural Network. Type Conference Article
  Year 2019 Publication 16th International Conference on Image Analysis and Recognition (ICIAR 2019); Waterloo, Canadá Abbreviated Journal  
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  Abstract Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a superesolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process a new thermal images dataset is used. Di?erent experiments have been carried out, ?rstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www.cidis.espol.edu.ec/es/dataset  
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  Call Number gtsi @ user @ Serial 103  
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Author Jorge Alvarez; Mireya Zapata; Dennys Paillacho pdf  openurl
  Title Mechanical Design of a spatial mechanism for the robot head movements in social robotics for the evaluation of Human-Robot Interaction. Type Conference Article
  Year 2019 Publication 2nd International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2019); Munich, Alemania Abbreviated Journal  
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  Call Number gtsi @ user @ Serial 104  
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Author Jorge Alvarez Tello; Mireya Zapata; Dennys Paillacho pdf  openurl
  Title Kinematic optimization of a robot head movements for the evaluation of human-robot interaction in social robotics. Type Conference Article
  Year 2019 Publication 10th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences (AHFE 2019), Washington D.C.; United States. Advances in Intelligent Systems and Computing Abbreviated Journal  
  Volume 975 Issue Pages 108-118  
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  Abstract This paper presents the simplification of the head movements from

the analysis of the biomechanical parameters of the head and neck at the

mechanical and structural level through CAD modeling and construction with

additive printing in ABS/PLA to implement non-verbal communication strategies and establish behavior patterns in the social interaction. This is using in the

denominated MASHI (Multipurpose Assistant robot for Social Human-robot

Interaction) experimental robotic telepresence platform, implemented by a

display with a fish-eye camera along with the mechanical mechanism, which

permits 4 degrees of freedom (DoF). In the development of mathematicalmechanical modeling for the kinematics codification that governs the robot and

the autonomy of movement, we have the Pitch, Roll, and Yaw movements, and

the combination of all of them to establish an active communication through

telepresence. For the computational implementation, it will be show the rotational matrix to describe the movement.
 
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  Call Number gtsi @ user @ Serial 108  
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Author Wilton Agila; Gomer Rubio; Francisco Vidal; B. Lima pdf  openurl
  Title Real time Qualitative Model for estimate Water content in PEM Fuel Cell Type Conference Article
  Year 2019 Publication 8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania Abbreviated Journal  
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  Abstract To maintain optimum performance of the electrical

response of a fuel cell, a real time identification of the

malfunction situations is required. Critical fuel cell states depend,

among others, on the variable demand of electric load and are

directly related to the membrane hydration level. The real time

perception of relevant states in the PEM fuel cell states space, is

still a challenge for the PEM fuel cell control systems. Current

work presents the design and implementation of a methodology

based upon fuzzy decision techniques that allows real time

characterization of the dehydration and flooding states of a PEM

fuel cell. Real time state estimation is accomplished through a

perturbation-perception process on the PEM fuel cell and further

on voltage oscillation analysis. The real time implementation of

the perturbation-perception algorithm to detect PEM fuel cell

critical states is a novelty and a step forwards the control of the

PEM fuel cell to reach and maintain optimal performance.
 
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 109  
Permanent link to this record
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