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Listar por autor "Elizondo Acuña, David Alberto"
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Aplicaciones de inteligencia artificial
Elizondo Acuña, David Alberto (2018-12-13)Las redes neuronales artificiales han sido usadas en innumerables problemas reales. Esta conferencia presenta un resumen de algunas de las aplicaciones más recientes de estas técnicas a problemas reales. Dentro de los ... -
Application of data augmentation techniques towards metabolomics
Moreno-Barea, Francisco J.; Franco, Leonardo; Elizondo Acuña, David Alberto; Grootveld, Martin (Elsevier, 2022-07-27)Niemann–Pick Class 1 (NPC1) disease is a rare and debilitating neurodegenerative lysosomal storage disease (LSD). Metabolomics datasets of NPC1 patients available to perform this type of analysis are often limited in the ... -
Foreground object detection enhancement by adaptive super resolution for video surveillance
Molina-Cabello, Miguel Ángel; Elizondo Acuña, David Alberto; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (2019-09-16)Foreground object detection is a fundamental low level task in current video surveillance systems. It is usually accomplished by keeping a model of the background at each frame pixel. Many background learning algorithms ... -
Homography estimation with deep convolutional neural networks by random color transformations
Molina-Cabello, Miguel Ángel; Elizondo Acuña, David Alberto; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (2019-09-13)Most classic approaches to homography estimation are based on the filtering of outliers by means of the RANSAC method. New proposals include deep convolutional neural networks. Here a new method for homography estimation ... -
Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning
Calderón-Ramírez, Saúl; Murillo-Hernández, Diego; Rojas-Salazar, Kevin; Calvo-Valverde, Luis-Alexander; Yang, Shengxiang; Moemeni, Armaghan; Elizondo Acuña, David Alberto; López-Rubio, Ezequiel; Molina-Cabello, Miguel Ángel[et al.] (2021-07)Computer aided diagnosis for mammogram images have seen positive results through the usage of deep learning architectures. However, limited sample sizes for the target datasets might prevent the usage of a deep learning ... -
Infering Air Quality from Traffic Data using Transferable Neural Network Models
Molina-Cabello, Miguel Ángel; Passow, Benjamin N.; Domínguez-Merino, Enrique; Elizondo Acuña, David Alberto; Obszynska, Jolanta (Springer, 2019-06)This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy ... -
Skin lesion classification by ensembles of deep convolutional networks and regularly spaced shifting
Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Elizondo Acuña, David Alberto (2021)Skin lesions are caused due to multiple factors, like allergies, infections, exposition to the sun, etc. These skin diseases have become a challenge in medical diagnosis due to visual similarities, where image classification ...