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Author Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero pdf  openurl
  Title Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. Type Conference Article
  Year 2018 Publication IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador Abbreviated Journal  
  Volume Issue Pages 1-6  
  Keywords  
  Abstract The identification of shrimp organs in biology using

histological images is a complex task. Shrimp histological images

poses a big challenge due to their texture and similarity among

classes. Image classification by using feature engineering and

convolutional neural networks (CNN) are suitable methods to

assist biologists when performing organ detection. This work

evaluates the Bag-of-Visual-Words (BOVW) and Pyramid-Bagof-

Words (PBOW) models for image classification leveraging big

data techniques; and transfer learning for the same classification

task by using a pre-trained CNN. A comparative analysis

of these two different techniques is performed, highlighting

the characteristics of both approaches on the shrimp organs

identification problem.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 87  
Permanent link to this record
 

 
Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud pdf  openurl
  Title Deep Learning based Single Image Dehazing Type Conference Article
  Year 2018 Publication 14th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2018. Salt Lake City, Utah. USA Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper proposes a novel approach to remove haze

degradations in RGB images using a stacked conditional

Generative Adversarial Network (GAN). It employs a triplet

of GAN to remove the haze on each color channel independently.

A multiple loss functions scheme, applied over a

conditional probabilistic model, is proposed. The proposed

GAN architecture learns to remove the haze, using as conditioned

entrance, the images with haze from which the clear

images will be obtained. Such formulation ensures a fast

model training convergence and a homogeneous model generalization.

Experiments showed that the proposed method

generates high-quality clear images.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 83  
Permanent link to this record
 

 
Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla pdf  url
openurl 
  Title Vegetation Index Estimation from Monospectral Images Type Conference Article
  Year 2018 Publication 15th International Conference, Image Analysis and Recognition (ICIAR 2018), Póvoa de Varzim, Portugal. Lecture Notes in Computer Science Abbreviated Journal  
  Volume 10882 Issue Pages 353-362  
  Keywords  
  Abstract This paper proposes a novel approach to estimate Normalized

Difference Vegetation Index (NDVI) from just the red channel of

a RGB image. The NDVI index is defined as the ratio of the difference

of the red and infrared radiances over their sum. In other words, information

from the red channel of a RGB image and the corresponding

infrared spectral band are required for its computation. In the current

work the NDVI index is estimated just from the red channel by training a

Conditional Generative Adversarial Network (CGAN). The architecture

proposed for the generative network consists of a single level structure,

which combines at the final layer results from convolutional operations

together with the given red channel with Gaussian noise to enhance

details, resulting in a sharp NDVI image. Then, the discriminative model

estimates the probability that the NDVI generated index came from the

training dataset, rather than the index automatically generated. Experimental

results with a large set of real images are provided showing that

a Conditional GAN single level model represents an acceptable approach

to estimate NDVI index.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 82  
Permanent link to this record
 

 
Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud pdf  openurl
  Title Near InfraRed Imagery Colorization Type Conference Article
  Year 2018 Publication 25 th IEEE International Conference on Image Processing, ICIP 2018 Abbreviated Journal  
  Volume Issue Pages 2237-2241  
  Keywords  
  Abstract This paper proposes a stacked conditional Generative

Adversarial Network-based method for Near InfraRed

(NIR) imagery colorization. We propose a variant architecture

of Generative Adversarial Network (GAN) that uses multiple

loss functions over a conditional probabilistic generative model.

We show that this new architecture/loss-function yields better

generalization and representation of the generated colored IR

images. The proposed approach is evaluated on a large test

dataset and compared to recent state of the art methods using

standard metrics.1

Index Terms—Convolutional Neural Networks (CNN), Generative

Adversarial Network (GAN), Infrared Imagery colorization.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 81  
Permanent link to this record
 

 
Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla pdf  url
openurl 
  Title Adaptive Harris Corners Detector Evaluated with Cross-Spectral Images Type Conference Article
  Year 2018 Publication International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing Abbreviated Journal  
  Volume 721 Issue Pages  
  Keywords  
  Abstract This paper proposes a novel approach to use cross-spectral

images to achieve a better performance with the proposed Adaptive Harris

corner detector comparing its obtained results with those achieved

with images of the visible spectra. The images of urban, field, old-building

and country category were used for the experiments, given the variety of

the textures present in these images, with which the complexity of the

proposal is much more challenging for its verification. It is a new scope,

which means improving the detection of characteristic points using crossspectral

images (NIR, G, B) and applying pruning techniques, the combination

of channels for this fusion is the one that generates the largest

variance based on the intensity of the merged pixels, therefore, it is that

which maximizes the entropy in the resulting Cross-spectral images.

Harris is one of the most widely used corner detection algorithm, so

any improvement in its efficiency is an important contribution in the

field of computer vision. The experiments conclude that the inclusion of

a (NIR) channel in the image as a result of the combination of the spectra,

greatly improves the corner detection due to better entropy of the

resulting image after the fusion, Therefore the fusion process applied to

the images improves the results obtained in subsequent processes such as

identification of objects or patterns, classification and/or segmentation.
 
  Address  
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  Publisher Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes 1 Approved no  
  Call Number gtsi @ user @ Serial 84  
Permanent link to this record
 

 
Author Wilton Agila; Gomer Rubio; L. Miranda; L. Vázquez pdf  openurl
  Title Qualitative Model of Control in the Pressure Stabilization of PEM Fuel Cell Type Conference Article
  Year 2018 Publication 7th International Conference on Renewable Energy Research and Applications, ICRERA 2018. Paris, Francia. Abbreviated Journal  
  Volume Issue Pages 1221-1226  
  Keywords  
  Abstract This work describes an approximate reasoning

technique to deal with the non-linearity that occurs in the

stabilization of the pressure of anodic and cathodic gases of a

proton exchange membrane fuel cell (PEM). The implementation

of a supervisory element in the stabilization of the pressure of the

PEM cell is described. The fuzzy supervisor is a reference

control, it varies the value of the reference given to the classic

low-level controller, Proportional – Integral – Derivative (PID),

according to the speed of change of the measured pressure and

the change in the error of the pressure. The objective of the fuzzy

supervisor is to achieve a rapid response over time of the variable

pressure, avoiding unwanted overruns with respect to the

reference value. A comparative analysis is detailed with the

classic PID control to evaluate the operation of the “fuzzy

supervisor”, with different flow values and different sizes of

active area of the PEM cell (electric power generated).
 
  Address  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 88  
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Author Gomer Rubio; Wilton Agila openurl 
  Title Dynamic Modeling of Fuel Cells in a Strategic Context Type Conference Article
  Year 2018 Publication 7th International Conference on Renewable Energy Research and Applications, ICRERA 2018. Paris, Francia. Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 86  
Permanent link to this record
 

 
Author Del Pino, J.; Salazar, G.; Cedeño, V. Msc. pdf  url
openurl 
  Title Adaptación de un Recomendador de Filtro Colaborativo Basado en el Usuario para la Creación de un Recomendador de Materias de Pregrado Basado en el Historial Académico de los Estudiantes Type Journal Article
  Year 2011 Publication Revista Tecnológica ESPOL Abbreviated Journal  
  Volume Vol. 24 Issue Pages pp. 29 - 34  
  Keywords  
  Abstract Los sistemas de recomendación son ampliamente utilizados hoy en día gracias a su capacidad de analizar las preferencias de usuarios y sugerir ítems. No obstante, el uso de los recomendadores está limitado a un modelo basado en el usuario y no en su historial de preferencias, discriminando así el campo de aplicación, por ejemplo, a sistemas académicos donde sea primordial el estudio de las decisiones del estudiante a lo largo de su carrera. El presente

trabajo presenta un esfuerzo por adaptar filtros colaborativos basados en el usuario a filtros colaborativos basados en el historial del usuario. Con un conjunto de pruebas mediremos su efectividad utilizando dos algoritmos distintos de similaridad para recomendar materias a un estudiante en el sexto semestre de la carrera de Ingeniería en Electrónica y Telecomunicaciones ofertada por la FIEC – ESPOL. Los resultados muestran que es factible adaptar un recomendador a un modelo basado en el historial del usuario
 
  Address Campus “Gustavo Galindo Velasco” La prosperina Km 30,5 vía perimetral, Guayaquil, Ecuador  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Español Summary Language Español Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 13  
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Author Arias Alexandra. Ing.; Peña Roxanna. Ing.; Chávez Patricia. MSEE.; Basurto Juan. Ing pdf  url
openurl 
  Title Análisis Comparativo de la Implementación de una PBX de Código Abierto instalada en un Servidor Tradicional y en un Enrutador Inalámbrico en términos de Calidad de Servicio en Redes Inalámbricas Amalladas Type Journal Article
  Year 2011 Publication Revista Tecnologica ESPOL RTE Abbreviated Journal  
  Volume Vol. 24 Issue Pages pp. 1-6  
  Keywords Redes Inalámbricas Mesh, VoIP, Asterisk  
  Abstract El presente trabajo compara dos Implementaciones de Centrales Telefónicas VoIP de Código Abierto implementados sobre una Red Inalámbrica Amallada. El primero comprende la instalación de la PBX en un servidor tradicional y el segundo la instalación de una PBX en un enrutador inalámbrico. Nuestro objetivo es

determinar cuál de estos dos sistemas es superior en cuanto a calidad de servicio se refiere. Para determinar la mejor solución, realizamos un estudio técnico de los paquetes capturados durante diferentes pruebas, considerando parámetros como el ancho de banda, retardo y jitter. Nuestros métodos de análisis pueden ser utilizados para futuros trabajos con una mayor complejidad y número de enrutadores inalámbrico, así como establecer el grado de afectación y el comportamiento de las dos PBX cuando haya congestión en la red.
 
  Address Escuela Superior Politécnica del Litoral Km 30.5 vía Perimetral  
  Corporate Author Thesis  
  Publisher Place of Publication Guayaquil, Guayas Ecuador Editor  
  Language Español Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 14  
Permanent link to this record
 

 
Author Carlos Monsalve; Alain April; Alain Abran pdf  url
openurl 
  Title BPM and requirements elicitation at multiple levels of abstraction: A review Type Conference Article
  Year 2011 Publication IADIS International Conference on Information Systems 2011 Abbreviated Journal  
  Volume Issue Pages 237-242  
  Keywords Business process modeling, levels of abstraction, requirements elicitation, requirements modeling, review  
  Abstract Business process models can be useful for requirements elicitation, among other things. Software development depends on the quality of the requirements elicitation activities, and so adequately modeling business processes (BPs) is critical. A key factor in achieving this is the active participation of all the stakeholders in the development of a shared vision of BPs.

Unfortunately, organizations often find themselves left with inconsistent BPs that do not cover all the stakeholders’ needs

and constraints. However, consolidation of the various stakeholder requirements may be facilitated through the use of multiple levels of abstraction (MLA). This article contributes to the research into MLA use in business process modeling (BPM) for software requirements by reviewing the theoretical foundations of MLA and their use in various BP-oriented approaches.
 
  Address CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL) Km. 30.5 vía Perimetral,  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 15  
Permanent link to this record
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