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Early Detection of Depression: Social Network Analysis and Random Forest Techniques 

Cacheda, Fidel; Fernández, Diego; Novoa, Francisco; Carneiro, Victor (J M I R Publications, Inc., 2019-06-10)
[Abstract] Background: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, ...
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Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment 

Liñares Blanco, José; Fernández-Lozano, Carlos (M D P I AG, 2019-07-31)
[Abstract]The prediction of metabolic activities in silico form is crucial to be able to address all research possibilities without exceeding the experimental costs. In particular, for cancer research, the prediction of ...
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NLOS Identification and Mitigation Using Low-Cost UWB Devices 

Barral Vales, Valentín; Escudero, Carlos J.; García-Naya, José A.; Maneiro-Catoira, Roberto (M D P I AG, 2019-08-08)
[Abstract] Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate ...
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Monitorización del estado de rodamientos basada en técnicas de aprendizaje automático 

Villalonga, Alberto; Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo; Matia, Fernando (Universidade da Coruña, Servizo de Publicacións, 2019)
[Resumen] En la actualidad, los procesos de fabricación están adoptando nuevas soluciones basadas en la aplicación de técnicas de aprendizaje automático, que permiten llevar a cabo la monitorización de los procesos en ...
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Application of Functional Data Analysis for the Prediction of Maximum Heart Rate 

Matabuena, Marcos; Vidal, Juan C.; Hayes, Philip R.; Saavedra-García, Miguel A.; Huelin Trillo, Fernando (IEEE-Institute of Electrical and Electronics Engineers, 2019-08-29)
[Abstract]: Maximum heart rate (MHR) is widely used in the prescription and monitoring of exercise intensity, and also as a criterion for the termination of sub-maximal aerobic _tness tests in clinical populations. Traditionally, ...
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Environmental Cross-Validation of NLOS Machine Learning Classification/Mitigation with Low-Cost UWB Positioning Systems 

Barral Vales, Valentín; Escudero, Carlos J.; García-Naya, José A.; Suárez-Casal, Pedro (M D P I AG, 2019-12-10)
[Abstract] Indoor positioning systems based on radio frequency inherently present multipath-related phenomena. This causes ranging systems such as ultra-wideband (UWB) to lose accuracy when detecting secondary propagation ...
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Ultra Wideband location in scenarios without clear line of sight: a practical approach 

Barral Vales, Valentín (2019)
[Abstract] Indoor location has experienced a major boost in recent years. location based services (LBS), which until recently were restricted to outdoor scenarios and the use of GPS, have also been extended into ...
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Using Artificial Vision Techniques for Individual Player Tracking in Sport Events 

López Castro, Roberto; Andrade, Diego (M D P I AG, 2019-07-31)
[Abstract] We introduce a hybrid approach that can track an individual football player in a video sequence. This solution achieves a good balance between speed and accuracy, combining traditional object tracking techniques ...
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Information Fusion and Ensembles in Machine Learning 

Seijo Pardo, Borja (2019)
[Abstract] Traditionally, machine learning methods have used a single learning model to solve a particular problem. However, the idea of combining multiple models instead of a single one to solve a problem has its rationale ...
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A Machine Learning Solution for Distributed Environments and Edge Computing 

Penas-Noce, Javier; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (M D P I AG, 2019-08-09)
[Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ...
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AuthorBarral Vales, Valentín (3)Fernández-Lozano, Carlos (3)Escudero, Carlos J. (2)García-Naya, José A. (2)Liñares Blanco, José (2)Andrade, Diego (1)Baamonde Álvarez, Sergio (1)Beruvides, Gerardo (1)Cabana, Martiño (1)Cacheda, Fidel (1)... View MoreSubject
Machine learning (14)
Aprendizaje automático (2)Cancer (2)Feature selection (2)UWB (2)Activity prediction (1)Análisis de datos funcionales (1)Artificial intelligence (1)Artificial neural networks (1)Artificial vision (1)... View MoreDate Issued
2019 (14)
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