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Computer Methods and Programs in Biomedicine(2)
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XII Jornadas Iberoamericanas de Ingenieria de Software e Ingenieria del Conocimiento 2017, JIISIC 2017 - Held Jointly with the Ecuadorian Conference on Software Engineering, CEIS 2017 and the Conference on Software Engineering Applied to Control and Automation Systems, ISASCA 2017(2)
Xii Jornadas Iberoamericanas De Ingenieria De Software E Ingenieria Del Conocimiento 2017 Jiisic 2017 Held Jointly with the Ecuadorian Conference on Software Engineering Ceis 2017 and the Conference on Software Engineering Applied to Control and Automation Systems Isasca 2017(2)
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scopus(12)
Atypical lymphoid cells circulating in blood in COVID-19 infection: morphology, immunophenotype and prognosis value
ArticleAbstract: AimsAtypical lymphocytes circulating in blood have been reported in COVID-19 patients. This study aiPalabras claves:immunophenotyping, Lymphocytes, morphological and microscopic findings, virusesAutores:Acevedo A., Bascón F., Boldú L., Díaz-Pavón M., Egri N., Juan M., Kevin Barrera, Laguna J., Merino A., Molina A., Rodellar J., Sibila O., Sibina F., Vlagea A.Fuentes:scopusAutomatic generation of artificial images of leukocytes and leukemic cells using generative adversarial networks (syntheticcellgan)
ArticleAbstract: Background and objectives: Visual analysis of cell morphology has an important role in the diagnosisPalabras claves:Blood cell automatic recognition, Blood cell synthetic images, convolutional neural networks, Deep learning, Generative Adversarial Networks, Image generationAutores:Kevin Barrera, Merino A., Molina A., Rodellar J.Fuentes:scopusA Deep Learning Approach for the Morphological Recognition of Reactive Lymphocytes in Patients with COVID-19 Infection
ArticleAbstract: Laboratory medicine plays a fundamental role in the detection, diagnosis and management of COVID-19Palabras claves:blood cell images, Cell morphology, convolutional neural networks, covid-19, deep learning, diagnosis, prognosis, reactive lymphocytesAutores:Alférez S., Boldú L., Kevin Barrera, Laguna J., Merino A., Molina A., Rodellar J.Fuentes:scopusComparation between free software (Python) and proprietary software (Matlab) for digital image processing, processing speed measurement and peripheral board control, applied to the monitoring of pyroclastic flows in eruptive processes
Conference ObjectAbstract: The digital image processing has its strength in the autonomy and robustness of a system to performPalabras claves:digital image processing, Eruptive process, matlab, PYTHONAutores:Christyan Cruz, Darío L. Mendoza, Francisco Xavier Viteri, Kevin Barrera, Kevin Iván Barrera LlangaFuentes:scopusUse of neural networks to the detection of pyroclastic flows in Ecuador volcanoes
Conference ObjectAbstract: Neural networks are oriented to provide solutions that require a complex computational solution andPalabras claves:neural network, Pyroclastic flows, VolcanoesAutores:Christyan Cruz, Darío L. Mendoza, Francisco Xavier Viteri, Kevin BarreraFuentes:scopusUsing computer vision techniques to generate embedded systems for monitoring volcanoes in Ecuador with Trajectory determination
ArticleAbstract: Ecuador is a country with a great number of volcanoes, 27 active in the part continental and insularPalabras claves:artificial vision, Autonomous, Embedded Systems, Noise inherent exist, Volcanic phenomenaAutores:Christyan Cruz, Darío L. Mendoza, Francisco Xavier Viteri, Kevin BarreraFuentes:scopusMDS-AN: An attention-based explainable model for detecting myelodysplastic syndrome using hematological variables
ArticleAbstract: Background and objectives: This study aims to develop and evaluate a deep learning model, which is bPalabras claves:Attention mechanisms, Deep learning, MDS automatic classification, Model explainability, Myelodysplastic syndrome (MDS), Post-hoc analysisAutores:Kevin Barrera, Marina Díaz-Beya, Merino A., Molina A., Rodellar J.Fuentes:scopusIdentification of abnormal conditions in induction motors from current spectrum images using a two-stage approach with progressive learning
ArticleAbstract: Background and objectives: This study presents a fault diagnosis system for induction machines basedPalabras claves:Convolutional neural network, Deep learning, fault diagnosis, Induction machine, Predictive maintenance, Visual geometry groupAutores:Ángel Sapena-Bañó, Javier Martínez-Román, Jordi Burriel-Valencia, Kevin BarreraFuentes:scopusFault Detection in Induction Machines Using Learning Models and Fourier Spectrum Image Analysis
ArticleAbstract: Induction motors are essential components in industry due to their efficiency and cost-effectivenessPalabras claves:Deep learning, Explainability, fault diagnosis, Induction Motors, Predictive maintenance, spectral imagesAutores:Ángel Sapena-Bañó, Javier Martínez-Román, Jordi Burriel-Valencia, Kevin BarreraFuentes:scopusA deep learning approach for automatic recognition of abnormalities in the cytoplasm of neutrophils
ArticleAbstract: Background and objectives: This study aims to develop and evaluate NeuNN, a system based on convolutPalabras claves:Blood cell automatic recognition, Blood cell morphology, convolutional neural networks, Cytoplasmic inclusions, Deep learning, Generative Adversarial Networks, neutrophilsAutores:Alférez S., Kevin Barrera, Merino A., Rodellar J.Fuentes:scopus