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Author Abel Rubio, Wilton Agila, Leandro González & Jonathan Aviles-Cedeno pdf  openurl
  Title (down) Distributed Intelligence in Autonomous PEM Fuel Cell Control. Type Journal Article
  Year 2023 Publication Energies 2023 Abbreviated Journal  
  Volume Vol. 16 Issue Issue 12 Pages  
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  Series Volume Series Issue Edition  
  ISSN 19961073 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 217  
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Author Ortiz J.; Londono J.; Novillo F.; Ampuno A.; Chávez M. pdf  url
openurl 
  Title (down) 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 Escuela Politécnica Nacional Place of Publication Editor  
  Language Español Summary Language Español Original Title  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 32  
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Author Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia url  doi
openurl 
  Title (down) Dense extreme inception network for edge detection. Type Journal Article
  Year 2023 Publication Pattern Recognition Abbreviated Journal  
  Volume Vol. 139 Issue Pages  
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  ISSN 00313203 ISBN Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 216  
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Author Henry Velesaca, Boris Vintimilla, Jorge Vulgarin, Coen Antens & Alberto Rubio Pérez openurl 
  Title (down) Deep Learning-based Multimodal Sensing Framework for AntiSpoofing Systems Type Journal Article
  Year 2024 Publication In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 238  
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Author Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title (down) Cross-Spectral Local Descriptors via Quadruplet Network Type Journal Article
  Year 2017 Publication In Sensors Journal Abbreviated Journal  
  Volume Vol. 17 Issue Pages pp. 873  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 64  
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Author Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa url  doi
openurl 
  Title (down) Corn Kernel Classification From Few Training Samples Type Journal Article
  Year 2023 Publication In journal Artificial Intelligence in Agriculture Abbreviated Journal  
  Volume Vol. 9 Issue Pages pp. 89-99  
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  Series Volume Series Issue Edition  
  ISSN 25897217 ISBN Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 223  
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Author Michael Teutsch, Angel Sappa & Riad Hammoud url  openurl
  Title (down) Computer Vision in the Infrared Spectrum: Challenges and ApproachesComputer Vision in the Infrared Spectrum: Challenges and Approaches Type Journal Article
  Year 2021 Publication Synthesis Lectures on Computer Vision Abbreviated Journal  
  Volume Vol. 10 No. 2 Issue Pages pp. 138  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 166  
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Author Velesaca, H.O., Suárez, P. L., Mira, R., & Sappa, A.D. pdf  openurl
  Title (down) Computer Vision based Food Grain Classification: a Comprehensive Survey Type Journal Article
  Year 2021 Publication In Computers and Electronics in Agriculture Journal. (Article number 106287) Abbreviated Journal  
  Volume Vol. 187 Issue Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 159  
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Author Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. pdf  openurl
  Title (down) Camera pose estimation in multi-view environments:from virtual scenarios to the real world Type Journal Article
  Year 2021 Publication In Image and Vision Computing Journal. (Article number 104182) Abbreviated Journal  
  Volume Vol. 110 Issue Pages  
  Keywords Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments  
  Abstract This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired

images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of

overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly

trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the

relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity

on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the

scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used,

highlighting the importance on the similarity between virtual-real scenarios.
 
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  Language English Summary Language English Original Title  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 147  
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Author Ulises Gildardo Quiroz Antúnez, Alejandro Ismael Monterroso Rivas, María Fernanda Calderón Vega, Adán Guillermo Ramírez García pdf  openurl
  Title (down) APTITUDE OF COFFEE (COFFEA ARABICA L.) AND CACAO (THEOBROMA CACAO L.) CROPS CONSIDERING CLIMATE CHANGE Type Journal Article
  Year 2022 Publication Granja Abbreviated Journal  
  Volume Vol. 36 Issue Issue 2 Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 200  
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