Listar 1. Investigación por autor "Rivero, Daniel"
Mostrando ítems 1-20 de 35
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A Public Domain Dataset for Real-Life Human Activity Recognition Using Smartphone Sensors
García-González, Daniel; Rivero, Daniel; Fernández-Blanco, Enrique; Rodríguez Luaces, Miguel (MDPI AG, 2020-04-13)[Abstract] In recent years, human activity recognition has become a hot topic inside the scientific community. The reason to be under the spotlight is its direct application in multiple domains, like healthcare or fitness. ... -
A review of artificial intelligence applied to path planning in UAV swarms
Puente-Castro, Alejandro; Rivero, Daniel; Pazos, A.; Fernández-Blanco, Enrique (Springer, 2021)[Abstract]: Path Planning problems with Unmanned Aerial Vehicles (UAVs) are among the most studied knowledge areas in the related literature. However, few of them have been applied to groups of UAVs. The use of swarms ... -
Application of Artificial Neural Networks for the Monitoring of Episodes of High Toxicity by DSP in Mussel Production Areas in Galicia
Molares-Ulloa, Andrés; Fernández-Blanco, Enrique; Rivero, Daniel (MDPI AG, 2020-08-19)[Abstract] This study seeks to support, through the use of Artificial Neural Networks (ANN), the decision to perform closings after days without sampling in the Vigo estuary. The opening and closing of the mussel production ... -
Applied Computational Techniques on Schizophrenia Using Genetic Mutations
Aguiar-Pulido, Vanessa; Gestal, M.; Fernández-Lozano, Carlos; Rivero, Daniel; Munteanu, Cristian-Robert (Bentham, 2013-03-01)[Abstract] Schizophrenia is a complex disease, with both genetic and environmental influence. Machine learning techniques can be used to associate different genetic variations at different genes with a (schizophrenic or ... -
Approach of Genetic Algorithms With Grouping Into Species Optimized With Predator-Prey Method for Solving Multimodal Problems
Seoane, Pablo; Gestal, M.; Dorado, Julián; Rabuñal, Juan R.; Rivero, Daniel (Springer, 2012)[Abstract] Over recent years, Genetic Algorithms have proven to be an appropriate tool for solving certain problems. However, it does not matter if the search space has several valid solutions, as their classic approach ... -
Aprendizaje basado en ejemplos: desarrollo de aplicaciones empresariales con tecnologías .net
Gestal, M.; Fernández-Blanco, Enrique; Rivero, Daniel; Vázquez-Naya, José; Rabuñal, Juan R.; Dorado, Julián; Pazos, A. (Universidad Peruana de Ciencias Aplicadas, 2015-06)[Resumen] El framework J2EE ha sido el gran dominador, durante mucho tiempo, en el desarrollo de aplicaciones empresariales. Esto hecho originó la aparición de un rico ecosistema de herramientas, manuales, tutoriales, ... -
Artificial cells for information processing: iris classification
Fernández-Blanco, Enrique; Dorado, Julián; Serantes, José Andrés; Rivero, Daniel; Rabuñal, Juan R. (Springer, 2011-06-01)[Abstract]: This paper presents a model in the Artificial Embryogene (AE) framework. The presented system tries to model the main functions of the biological cell model. The main part of this paper describes the Gene ... -
Automated Early Detection of Drops in Commercial Egg Production Using Neural Networks
Ramírez-Morales, Iván; Fernández-Blanco, Enrique; Rivero, Daniel; Pazos, A. (Taylor & Francis, 2017-10-17)[Abstract] 1. The purpose of this work was to support decision-making in poultry farms by performing automatic early detection of anomalies in egg production. 2. Unprocessed data were collected from a commercial egg ... -
Automatic Seizure Detection Based on Star Graph Topological Indices
Fernández-Blanco, Enrique; Rivero, Daniel; Rabuñal, Juan R.; Dorado, Julián; Pazos, A.; Munteanu, Cristian-Robert (Elsevier, 2012-08-15)[Abstract] The recognition of seizures is very important for the diagnosis of patients with epilepsy. The seizure is a process of rhythmic discharge in brain and occurs rarely and unpredictably. This behavior generates a ... -
Biomedical data integration in computational drug design and bioinformatics
Seoane, José A.; Aguiar-Pulido, Vanessa; Munteanu, Cristian-Robert; Rivero, Daniel; Rabuñal, Juan R.; Dorado, Julián; Pazos, A. (Bentham Science, 2013)[Abstract In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real ... -
Classical Music Prediction and Composition by Means of Variational Autoencoders
Rivero, Daniel; Ramírez-Morales, Iván; Fernández-Blanco, Enrique; Ezquerra, Noberto; Pazos, A. (MDPI AG, 2020-04-27)[Abstract] This paper proposes a new model for music prediction based on Variational Autoencoders (VAEs). In this work, VAEs are used in a novel way to address two different issues: music representation into the latent ... -
Classification of Signals by Means of Genetic Programming
Fernández-Blanco, Enrique; Rivero, Daniel; Gestal, M.; Dorado, Julián (Springer, 2013-03-30)[Abstract] This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. ... -
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
Fernández-Blanco, Enrique; Rivero, Daniel; Pazos, A. (Springer Nature, 2019-06-26)[Abstract] Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ... -
Deep learning models for real-life human activity recognition from smartphone sensor data
García-González, Daniel; Rivero, Daniel; Fernández-Blanco, Enrique; Rodríguez Luaces, Miguel (Elsevier, 2023-12)[Abstract]: Nowadays, the field of human activity recognition (HAR) is a remarkably hot topic within the scientific community. Given the low cost, ease of use and high accuracy of the sensors from different wearable devices ... -
Desarrollo y simplificación de redes de neuronas artificiales mediante el uso de técnicas de computación evolutiva
Rivero, Daniel (2007)[Resumen] Esta Tesis propone el uso de técnicas de Computación Evolutiva (CE) con el objetivo de automatizar el proceso de desarrollo de Redes de Neuronas Artificiales (RR,NN.AA.). Tradicionalmente, el desarrollo de ... -
Detection of Bovine Mastitis in Raw Milk, Using a Low-Cost NIR Spectrometer and k-NN Algorithm
Ramírez Morales, Iván; Aguilar, Lenin; Fernández-Blanco, Enrique; Rivero, Daniel; Pérez, Jhonny; Pazos, A. (MDPI, 2021)[Abstract] Among the bovine diseases, mastitis causes high economic losses in the dairy production system. Nowadays, detection under field conditions is mainly performed by the California Mastitis Test, which is considered ... -
Detection of Chocolate Properties Using Near-Infrared Spectrophotometry †
Galdo, Brais; Fernández-Blanco, Enrique; Rivero, Daniel (MDPI, 2021)[Abstract] Knowing the chemical composition of a substance provides valuable information about it. That is why numerous techniques have been developed to try to obtain it. One of them is the Near Infrared Spectrometry ... -
Determination of Egg Storage Time at Room Temperature Using a Low-Cost NIR Spectrometer and Machine Learning Techniques
Coronel-Reyes, Julián; Ramírez-Morales, Iván; Fernández-Blanco, Enrique; Rivero, Daniel; Pazos, A. (Elsevier, 2017-12-21)[Abstract] Currently, consumers are more concerned about freshness and quality of food. Poultry egg storage time is a freshness and quality indicator in industrial and consumer applications, even though egg marking is not ... -
Development of a Server for the Implementation of Data Processing Pipelines and ANN Training
Galdo, Brais; Rivero, Daniel (MDPI, 2021)[Abstract] Data processing and the use of machine learning techniques make it possible to solve a wide variety of problems. The great disadvantage of using this type of technology is the enormous amount of computation ... -
DoME: A Deterministic Technique for Equation Development and Symbolic Regression
Rivero, Daniel; Fernández-Blanco, Enrique; Pazos, A. (Elsevier, 2022-03-04)[Abstract] Based on a solid mathematical background, this paper proposes a method for Symbolic Regression that enables the extraction of mathematical expressions from a dataset. Contrary to other approaches, such as Genetic ...