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Listar por palabra clave "Deep learning"

Mostrando ítems 1-20 de 333

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A Cloud-Based Framework for Machine Learning Workloads and Applications

Lopez Garcia, Alvaro; Marco De Lucas, Jesús; Antonacci, Marica; Zu Castell, Wolfgang; David, Mario; Hardt, Marcus; Lloret Iglesias, Lara; Moltó, Germán; Plociennik, Marcin; Tran, Viet; Alic, Andrei Stefan; Caballer Fernández, Miguel; Campos Plasencia, Isabel; Costantini, Alessandro; Dlugolinsky, Stefan (Institute of Electrical and Electronics Engineers, 2020-01-06)

[EN] In this paper we propose a distributed architecture to provide machine learning practitioners with a set of tools and cloud services that cover the whole machine learning development cycle: ranging from the models ...
A Comparative Analysis of Deep Learning Convolutional Neural Network Architectures for Fault Diagnosis of Broken Rotor Bars in Induction Motors

Barrera-Llanga, Kevin; Burriel-Valencia, Jordi; Sapena-Bano, Angel; Martinez-Roman, Javier (MDPI AG, 2023-10)

[EN] Induction machines (IMs) play a critical role in various industrial processes but are susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic techniques are essential in addressing these ...
A comparative study of Neural Machine Translation frameworks for the automatic translation of open data resources

Iranzo Sánchez, Javier (Universitat Politècnica de València, 2018-09-11)

[EN] Machine Translation (MT) is one of the most active areas in Artificial Intelligence, particularly in Pattern Recognition. MT has recently received a great deal of attention by key technology players such as Google, ...
A comparison of Covid-19 early detection between convolutional neural networks and radiologists

Albiol Colomer, Alberto; Albiol, Francisco; Paredes Palacios, Roberto; Plasencia-Martínez, Juana María; Blanco Barrio, Ana; García Santos, José M.; Tortajada, Salvador; González Montaño, Victoria M.; Rodríguez Godoy, Clara E.; Fernández Gómez, Saray; Oliver-Garcia, Elena; de la Iglesia Vayá, María; Márquez Pérez, Francisca L.; Rayo Madrid, Juan I. (SpringerOpen, 2022-07-28)

[EN] Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting ...
A Deep Learning Approach for Featureless Robust Quality Assessment of Intermittent Atrial Fibrillation Recordings from Portable and Wearable Devices

Huerta Herraiz, Álvaro; Martínez-Rodrigo, Arturo; Bertomeu-González, Vicente; Quesada, Aurelio; Rieta, J J; Alcaraz, Raúl (MDPI AG, 2020-07)

[EN] Atrial fibrillation (AF) is the most common heart rhythm disturbance in clinical practice. It often starts with asymptomatic and very short episodes, which are extremely difficult to detect without long-term monitoring ...
A deep Learning approach for reconstructing 3D turbulent flows from 2D observation data

Yousif, Mustafa Z.; Yu, Linqui; Hoyas, S.; Vinuesa, Ricardo; Lim, Hee-Chang (Nature Publishing Group, 2023-02-13)

[EN] Turbulence is a complex phenomenon that has a chaotic nature with multiple spatio-temporal scales, making predictions of turbulent flows a challenging topic. Nowadays, an abundance of high-fidelity databases can be ...
A Deep Learning Framework to classify Breast Density with Noisy Labels Regularization

López-Almazán, Héctor; Perez-Benito, Francisco Javier; Larroza, Andrés; Perez-Cortes, Juan-Carlos; Pollán, Marina; Perez-Gomez, Beatriz; Salas-Trejo, Dolores; Casals, María; Llobet Azpitarte, Rafael (Elsevier, 2022-06-01)

[EN] Background and Objective: Breast density assessed from digital mammograms is a biomarker for higher risk of developing breast cancer. Experienced radiologists assess breast density using the Breast Image and Data ...
A Deep Learning Model for Markerless Pose Estimation Based on Keypoint Augmentation: What Factors Influence Errors in Biomechanical Applications?

RUESCAS NICOLAU, ANA VIRGINIA; Medina Ripoll, Enrique; De Rosario Martínez, Helios; Sanchiz Navarro, Joaquin; Parrilla Bernabé, Eduardo; Juan, M.-Carmen (MDPI AG, 2024-03)

[EN] In biomechanics, movement is typically recorded by tracking the trajectories of anatomical landmarks previously marked using passive instrumentation, which entails several inconveniences. To overcome these disadvantages, ...
A deep learning model to predict lower temperatures in agriculture

Guillén-Navarro, Miguel A.; Martínez-España, Raquel; Llanes, Antonio; Bueno-Crespo, Andrés; Cecilia-Canales, José María (IOS Press, 2020)

[EN] Deep learning techniques provide a novel framework for prediction and classification in decision-making procedures that are widely applied in different fields. Precision agriculture is one of these fields where the ...
A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation

Perez-Benito, Francisco Javier; Signol, François; Perez-Cortes, Juan-Carlos; Fuster Bagetto, Alejandro; Pollan, Marina; Pérez-Gómez, Beatriz; Salas-Trejo, Dolores; Casals, Maria; Martínez, Inmaculada; Llobet Azpitarte, Rafael (Elsevier, 2020-10)

[EN] Background and Objective: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic ...
A GRU deep learning system against attacks in software defined networks

Assis, Marcos V.O.; Carvalho, Luiz F.; Lloret, Jaime; Proença Jr, Mario L. (Elsevier, 2021-03-01)

[EN] The management of modern network environments is becoming more and more complex due to new requirements of devices' heterogeneity regarding the popularization of the Internet of Things (IoT), as well as the dynamic ...
A happiness degree predictor using the conceptual data structure for deep learning architectures

Perez-Benito, Francisco Javier; Villacampa-Fernandez, Patricia; Conejero, J. Alberto; Garcia-Gomez, Juan M; NAVARRO-PARDO, ESPERANZA (Elsevier, 2019-01)

[EN] Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the ...
A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

Peñaranda-Cebrián, Cristian; Reaño, Carlos; Silla, Federico (MDPI AG, 2024-07)

[EN] GPUs are commonly used to accelerate the execution of applications in domains such as deep learning. Deep learning applications are applied to an increasing variety of scenarios, with edge computing being one of them. ...
A Spanish dataset for reproducible benchmarked offline handwriting recognition

España Boquera, Salvador; Castro-Bleda, Maria Jose (Springer-Verlag, 2022-09)

[EN] In this paper, a public dataset for Offline Handwriting Recognition, along with an appropriate evaluation method to provide benchmark indicators at sentence level, is presented. This dataset, called SPA-Sentences, ...
A Study of Deep Learning Methods for Image Classification

Xinyu, Li (Universitat Politècnica de València, 2022-05-10)

[ES] En este proyecto se implementarán métodos de aprendizaje profundo basados en redes neuronales convolucionales (CNN) para problemas de clasificación de imágenes. El aprendizaje profundo (AP) es un enfoque ...
A Study on Image Data Augmentation for Classification Based on Deep Learning

Yu, Cenhua (Universitat Politècnica de València, 2024-09-26)

[ES] Este proyecto implementará varias técnicas de aumento de datos de imágenes para su clasificación mediante aprendizaje profundo. Esas técnicas son necesarias cuando la cantidad de muestras de datos etiquetadas disponibles ...
A Study on Image Denoising Using Deep Learning

Lin, Guanyi (Universitat Politècnica de València, 2024-09-26)

[ES] Este proyecto implementará varias técnicas de eliminación de ruido de datos de imágenes para su clasificación mediante aprendizaje profundo. Este es un tema importante a resolver para mejorar la calidad de las imágenes ...
Accelerating distributed deep neural network training with pipelined MPI allreduce

Castelló, Adrián; Quintana-Ortí, Enrique S.; Duato Marín, José Francisco (Springer-Verlag, 2021-12)

[EN] TensorFlow (TF) is usually combined with the Horovod (HVD) workload distribution package to obtain a parallel tool to train deep neural network on clusters of computers. HVD in turn utilizes a blocking Allreduce ...
Active methodologies for deep learning in sustainable development goals

Romero Gil, Inmaculada; Paches Giner, Maria Aguas Vivas; Sebastiá-Frasquet, M.-T.; Hernández Crespo, Carmen (IATED Academy, 2021-03-09)

[EN] The general objective of this project was to improve the quality of student learning, from the point of view of a global objective, sustainable development, and therefore aligned with the SDGs (Sustainable Development ...
Adoption Factors of Artificial intelligence in Human Resource Management

Tuffaha, Mohand (Universitat Politècnica de València, 2022-09-06)

[ES] El mundo es testigo de nuevos avances tecnológicos que afectan significativamente a las organizaciones en diferentes departamentos. La inteligencia artificial (IA) es uno de estos avances, visto como una tecnología ...