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Author Henry Velesaca Lara, Patricia Suarez, Darío Carpio & Angel Sappa pdf  url
openurl 
  Title Fruit Grading based on Deep Learning and Active Vision System Type Conference Article
  Year 2024 Publication Second International Conference of Applied Industrial Engineering: Intelligent Production Automation and its Sustainable Development (CIIA 2024) Abbreviated Journal  
  Volume Vol. 532 Issue Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 241  
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Author Henry Velesaca Lara, Juan Antonio Holgado & José Miguel Gutiérrez pdf  url
openurl 
  Title Optimizing Smart Factory Operations: A Methodological Approach to Industrial System Implementation based on OPC-UA Type Conference Article
  Year 2024 Publication Second International Conference of Applied Industrial Engineering: Intelligent Production Automation and its Sustainable Development (CIIA 2024) Abbreviated Journal  
  Volume Vol. 532 Issue Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 242  
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Author Patricia Suarez, Angel Sappa openurl 
  Title Depth-Conditioned Thermal-like Image Generation Type Conference Article
  Year 2024 Publication Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 243  
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Author Omar Coello, Moisés Coronel, Darío Carpio, Boris X. Vintimilla & Luis Chuquimarca openurl 
  Title Enhancing Apple’s Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging Type Conference Article
  Year 2024 Publication Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 244  
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Author Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin openurl 
  Title Classifying Healthy and Defective Fruits with a Siamese Architecture and CNN Models Type Conference Article
  Year 2024 Publication Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) Abbreviated Journal  
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  Call Number cidis @ cidis @ Serial 245  
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Author Jácome Galarza, Luis Roberto openurl 
  Title Estimation of Corn Crop Yield using Multimodal Deep Learning from Multispectral Images and Environmental Sensors Type Conference Article
  Year 2024 Publication In accepted in 19ª Conferência Ibérica de Sistemas e Tecnologias de Informação; CISTI'2024 Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 246  
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Author Patricia L. Suarez, Dario Carpio, Angel D. Sappa pdf  openurl
  Title Enhancement of Guided Thermal Image Super-Resolution Approaches Type Journal
  Year 2024 Publication Neurocomputing Abbreviated Journal  
  Volume 573 Issue Pages  
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  Area Expedition Conference Neurocomputing  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 247  
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Author Mildred Cruz; Cristhian A. Aguilera; Boris X. Vintimilla; Ricardo Toledo; Ángel D. Sappa pdf  openurl
  Title Cross-spectral image registration and fusion: an evaluation study Type Conference Article
  Year 2015 Publication 2nd International Conference on Machine Vision and Machine Learning Abbreviated Journal  
  Volume 331 Issue Pages  
  Keywords multispectral imaging; image registration; data fusion; infrared and visible spectra  
  Abstract This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented.  
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  Publisher (up) Computer Vision Center Place of Publication Barcelona, Spain Editor  
  Language English Summary Language English Original Title  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 35  
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Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic pdf  url
openurl 
  Title Sensor Fault Detection and Diagnosis for autonomous vehicles Type Conference Article
  Year 2015 Publication 2nd International Conference on Mechatronics, Automation and Manufacturing (ICMAM 2015), International Conference on, Singapur, 2015 Abbreviated Journal  
  Volume 30 Issue MATEC Web of Conferences Pages 1-6  
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  Abstract In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.  
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  Publisher (up) EDP Sciences Place of Publication Editor  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 42  
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Author Ortiz J.; Londono J.; Novillo F.; Ampuno A.; Chávez M. pdf  url
openurl 
  Title Determinación de Invariantes en Grandes Centros de Datos basados en Topología Fat-Tree Type Journal Article
  Year 2015 Publication Revista Politécnica Abbreviated Journal  
  Volume Vol. 35 Issue Pages pp. 91-96  
  Keywords Invariantes de red, topologías, Fat-tree, simulación, emulación  
  Abstract Durante los últimos años ha existido un fuerte incremento en el acceso a internet, causando que los centros de datos ( DC) deban adaptar dinámicamente su infraestructura de red de cara a enfrentar posibles problemas de congestión, la cual no siempre se da de forma oportuna. Ante esto, nuevas topologías de red se han propuesto en los últimos años, como una forma de brindar mejores condiciones para el manejo de tráfico interno, sin embargo es común que para el estudio de estas mejoras, se necesite recrear el comportamiento de un verdadero DC en modelos de simulación/emulación. Por lo tanto se vuelve esencial validar dichos modelos, de cara a obtener resultados coherentes con la realidad. Esta validación es posible por medio de la identificación de ciertas propiedades que se deducen a partir de las variables y los parámetros que describen la red, y que se mantienen en las topologías de los DC para diversos escenarios y/o configuraciones. Estas propiedades, conocidas como invariantes, son una expresión del funcionamiento de la red en ambientes reales, como por ejemplo la ruta más larga entre dos nodos o el número de enlaces mínimo que deben fallar antes de una pérdida de conectividad en alguno de los nodos de la red. En el presente trabajo se realiza la identificación, formulación y comprobación de dos invariantes para la topología Fat-Tree, utilizando como software emulador a mininet. Las conclusiones muestran resultados concordantes entre lo analítico y lo práctico.  
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  Publisher (up) Escuela Politécnica Nacional Place of Publication Editor  
  Language Español Summary Language Español Original Title  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 32  
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