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| Author | Alex Ferrin; Julio Larrea; Miguel Realpe; Daniel Ochoa | ||||
| Title | Detection of utility poles from noisy Point Cloud Data in Urban environments. | Type | Conference Article | ||
| Year | 2018 | Publication | Artificial Intelligence and Cloud Computing Conference (AICCC 2018) | Abbreviated Journal | |
| Volume | Issue | Pages | 53-57 | ||
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| Abstract | In recent years 3D urban maps have become more common, thus providing complex point clouds that include diverse urban furniture such as pole-like objects. Utility poles detection in urban environment is of particular interest for electric utility companies in order to maintain an updated inventory for better planning and management. The present study develops an automatic method for the detection of utility poles from noisy point cloud data of Guayaquil – Ecuador, where many poles are located next to buildings, or houses are built until the border of the sidewalk getting very close to poles, which increases the difficulty of discriminating poles, walls, columns, fences and building corners. | ||||
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| Call Number | gtsi @ user @ | Serial | 94 | ||
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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 | 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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Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 129 | ||
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| Author | Armin Mehri; Angel D. Sappa | ||||
| 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 | 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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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 105 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud | ||||
| 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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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 106 | ||
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| Author | Angel Morera; Angel Sánchez; Angel D. Sappa; José F. Vélez | ||||
| 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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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 107 | ||
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| Author | José Reyes; Axel Godoy; Miguel Realpe. | ||||
| 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 | |
| Volume | 2019-July | Issue | Pages | ||
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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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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 102 | ||
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| Author | Rafael E. Rivadeneira; Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla. | ||||
| 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 | |
| Volume | Issue | Pages | 417-426 | ||
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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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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 103 | ||
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| Author | Jorge Alvarez; Mireya Zapata; Dennys Paillacho | ||||
| 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 | |
| Volume | 1026 | Issue | Pages | 160-165 | |
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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 104 | ||
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| Author | Jorge Alvarez Tello; Mireya Zapata; Dennys Paillacho | ||||
| 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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Approved | yes | |||
| Call Number | gtsi @ user @ | Serial | 108 | ||
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| Author | Wilton Agila; Gomer Rubio; Francisco Vidal; B. Lima | ||||
| 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 | |
| Volume | Issue | Pages | 455-459 | ||
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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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Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 109 | ||
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