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Browsing by Subject "Deep learning"

Now showing items 1-20 of 213

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 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 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 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 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 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 ...
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 ...
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models

Magnossao de Paula, Angel Felipe; Baris Schlicht, Ipek (CEUR Workshop, 2021-09-21)

[EN] This paper describes our participation in the DEtection of TOXicity in comments In Spanish (DETOXIS) shared task 2021 at the 3rd Workshop on Iberian Languages Evaluation Forum. The shared task is divided into two ...
An emotion and cognitive based analysis of mental health disorders from social media data

Uban, Ana-Sabina; Chulvi-Ferriols, María Alberta; Rosso, Paolo (Elsevier, 2021-11)

[EN] Mental disorders can severely affect quality of life, constitute a major predictive factor of suicide, and are usually underdiagnosed and undertreated. Early detection of signs of mental health problems is particularly ...
Analysis of a deep learning algorithm to detect R peaks in ECG signals

Lafuente Alcázar, Beatriz (Universitat Politècnica de València, 2022-07-14)

[EN] Biomedical signals are a result of cells’ electrical activity, and the changes in their voltage. Electrocardiogram (ECG) signals are a specific type of biosignals, and they represent the main diagnostic tool for ...
Análisis de audio mediante técnicas de aprendizaje profundo

Pastor Naranjo, Francisco (Universitat Politècnica de València, 2022-10-14)

[ES] El análisis de la señal de audio puede definirse como el proceso de extracción de información relevante a partir de las muestras de la señal. En la mayoría de los casos, las señales de voz y música son captadas por ...
Análisis de las prestaciones del entorno de deep learning TensorFlow

Rodríguez Alepuz, Sergio (Universitat Politècnica de València, 2018-09-11)

[ES] Los sistemas de aprendizaje automático —y, en concreto, los modelos de aprendizaje profundo (del inglés, deep learning) o redes neuronales— se han popularizado recientemente debido a que han supuesto un salto ...
Anomalous Diffusion Characterization using Machine Learning Methods

Garibo Orts, Óscar (Universitat Politècnica de València, 2023-04-18)

[ES] Durante las últimas décadas el uso del aprendizaje automático (machine learning) y de la inteligencia artificial ha mostrado un crecimiento exponencial en muchas áreas de la ciencia. El hecho de que los ordenadores ...
Anxiety towards Statistics and Its Relationship with Students' Attitudes and Learning Approach

Peiró Signes, Angel; Trull, Oscar; Segarra-Oña, Marival; García-Díaz, J. Carlos (MDPI AG, 2021-03)

[EN] Many university students have difficulties when facing statistics related tasks, leading to an increase in their levels of anxiety and poor performance. Researchers have identified negative attitudes towards statistics, ...
APLICACIONES DE GPUs EN VISIÓN E INTELIGENCIA ARTIFICIAL PARA EL RECONOCIMIENTO DE FORMAS

Giménez Campos, Javier (Universitat Politècnica de València, 2021-10-11)

[ES] Para la realización del trabajo se recurrirá a la programación, mediante el lenguaje de programación Python, del uso de una GPU donde se realizará la identificación de un objeto, por ejemplo, en este caso se realizará ...