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Author (up) Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title Learning crossspectral similarity measures with deep convolutional neural networks Type Conference Article
  Year 2016 Publication IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops Abbreviated Journal  
  Volume Issue Pages 267-275  
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  Abstract The simultaneous use of images from different spectra can be helpful to improve the performance of many com- puter vision tasks. The core idea behind the usage of cross- spectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN archi- tectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Ex- perimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Ad- ditionally, our experiments show that some CNN architec- tures are capable of generalizing between different cross- spectral domains.  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 48  
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Author (up) Cristhian A. Aguilera; Xaver Soria; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title RGBN Multispectral Images: a Novel Color Restoration Approach Type Conference Article
  Year 2017 Publication 15th International Conference on Practical Applications of Agents and Multi-Agent Systems Abbreviated Journal  
  Volume 619 Issue Pages 155-163  
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  Call Number cidis @ cidis @ Serial 59  
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Author (up) Cristina L. Abad; Yi Lu; Roy H. Campbell pdf  url
openurl 
  Title DARE: Adaptive Data Replication for Efficient Cluster Scheduling Type Conference Article
  Year 2011 Publication IEEE International Conference on Cluster Computing, 2011 Abbreviated Journal  
  Volume Issue Pages 159 - 168  
  Keywords MapReduce, replication, scheduling, locality  
  Abstract Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively.  
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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 21  
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Author (up) Daniela Rato, Miguel Oliviera, Victor Santos, Manuel Gomes & Angel Sappa url  openurl
  Title A Sensor-to-Pattern Calibration Framework for Multi-Modal Industrial Collaborative Cells. Type Journal Article
  Year 2022 Publication Journal of Manufacturing Systems Abbreviated Journal  
  Volume Vol. 64 Issue Pages pp. 497-507  
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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 184  
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Author (up) 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  
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  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  
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  Language Español Summary Language Español Original Title  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 13  
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Author (up) Dennis G. Romero, Anselmo Frizera N., & Teodiano Freire B. pdf  url
openurl 
  Title Reconocimiento en-línea de acciones humanas basado en patrones de RWE aplicado en ventanas dinámicas de momentos invariantes. Type Journal Article
  Year 2014 Publication Revista Iberoamericana de Automática e Informática industrial 00 (2014) Abbreviated Journal  
  Volume Vol. 11 Issue Pages pp. 202-211  
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  Call Number cidis @ cidis @ Serial 220  
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Author (up) Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla pdf  openurl
  Title RWE patterns extraction for on-line human action recognition through window-based analysis of invariant moments Type Conference Article
  Year 2012 Publication 5th Workshop in applied Robotics and Automation (RoboControl) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Human action recognition, Relative Wavelet Energy, Window-based temporal analysis.  
  Abstract This paper presents a method for on-line human action recognition on video sequences. An analysis based on Mahalanobis distance is performed to identify the “idle” state, which defines the beginning and end of the person movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.  
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  Call Number cidis @ cidis @ Serial 23  
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Author (up) Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla pdf  url
openurl 
  Title An approach to automatic assistance in physiotherapy based on on-line movement identification. Type Conference Article
  Year 2012 Publication VI Andean Region International Conference – ANDESCON 2012 Abbreviated Journal  
  Volume Issue Pages  
  Keywords patient rehabilitation, patient treatment, statistical analysis  
  Abstract This paper describes a method for on-line movement identification, oriented to patient’s movement evaluation during physiotherapy. An analysis based on Mahalanobis distance between temporal windows is performed to identify the “idle/motion” state, which defines the beginning and end of the patient’s movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.  
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  Publisher IEEE Place of Publication Andean Region International Conference (ANDESCON), 2012 VI Editor  
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  Call Number cidis @ cidis @ Serial 24  
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Author (up) Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos pdf  url
openurl 
  Title A predictive model for human activity recognition by observing actions and context Type Conference Article
  Year 2015 Publication ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015 Abbreviated Journal  
  Volume Issue Pages 323 - 333  
  Keywords Edge width, Image blu,r Defocus map, Edge model  
  Abstract This paper presents a novel model to estimate human activities – a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach.  
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  Call Number cidis @ cidis @ Serial 43  
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Author (up) Dennis G. Romero; Roberto Yoncon; Angel Guale; Bonny Bayot; Fanny Panchana pdf  openurl
  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 1-6  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 61  
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