Listar por autor "Rivero, Daniel"
Mostrando ítems 21-36 de 36
-
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 ... -
Early Warning in Egg Production Curves from Commercial Hens: a SVM Approach
Ramírez-Morales, Iván; Rivero, Daniel; Fernández-Blanco, Enrique; Pazos, A. (Elsevier, 2016-01-02)[Abstract] Artificial Intelligence allows the improvement of our daily life, for instance, speech and handwritten text recognition, real time translation and weather forecasting are common used applications. In the livestock ... -
EEG Signal Processing with Separable Convolutional Neural Network for Automatic Scoring of Sleeping Stage
Fernández-Blanco, Enrique; Rivero, Daniel; Pazos, A. (Elsevier, 2020-06-01)[Abstract] Nowadays, among the Deep Learning works, there is a tendency to develop networks with millions of trainable parameters. However, this tendency has two main drawbacks: overfitting and resource consumption due ... -
Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning
Galdo, Brais; Rivero, Daniel; Fernández-Blanco, Enrique (M D P I AG, 2019-08-13)[Abstract] It is a fact that, non-destructive measurement technologies have gain a lot of attention over the years. Among those technologies, NIR technology is the one which allows the analysis of electromagnetic spectrum ... -
Example-Based Learning: Development of Business Applications witn .Net Technologies
Gestal, M.; Vázquez-Naya, José; Fernández-Blanco, Enrique; Rivero, Daniel; Rabuñal, Juan R.; Dorado, Julián; Pazos, A. (Universidad Peruana de Ciencias Aplicadas, 2015-06)[Abstract] For a long time, J2EE has been the dominating framework for the development of business applications. This fact resulted in a rich ecosystem of tools, manuals, tutorials, etc. that explain different implementation ... -
Introducing a Human Activity Recognition Dataset Gathered on Real-Life Conditions
García-González, Daniel; Fernández-Blanco, Enrique; Rivero, Daniel; Rodríguez Luaces, Miguel (Universidade da Coruña, Servizo de Publicacións, 2023)[Abstract] Human activity recognition (HAR) has garnered significant scientific interest in recent years. The widespread use of smartphones enabled convenient and cost-effective data collection, eliminating the need for ... -
Machine Learning in Management of Precautionary Closures Caused by Lipophilic Biotoxins
Molares-Ulloa, Andrés; Fernández-Blanco, Enrique; Pazos, A.; Rivero, Daniel (Elsevier, 2022)[Abstract] Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galicia, the Spanish main producer ... -
New machine learning approaches for real-life human activity recognition using smartphone sensor-based data
García-González, Daniel; Rivero, Daniel; Fernández-Blanco, Enrique; Rodríguez Luaces, Miguel (Elsevier B.V., 2023)[Abstract]: In recent years, mainly due to the application of smartphones in this area, research in human activity recognition (HAR) has shown a continuous and steady growth. Thanks to its wide range of sensors, its size, ... -
Optimization of NIR Calibration Models for Multiple Processes in the Sugar Industry
Ramírez-Morales, Iván; Rivero, Daniel; Fernández-Blanco, Enrique; Pazos, A. (Elsevier, 2016-10-14)[Abstract] The measurements of Near-Infrared (NIR) Spectroscopy, combined with data analysis techniques, are widely used for quality control in food production processes. This paper presents a methodology to optimize ... -
Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming
Rivero, Daniel; Fernández-Blanco, Enrique; Fernández-Lozano, Carlos; Pazos, A. (Taylor & Francis Group, 2019-07-31)[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of ... -
Q-Learning based system for Path Planning with Unmanned Aerial Vehicles swarms in obstacle environments
Puente-Castro, Alejandro; Rivero, Daniel; Pedrosa, Eurico; Pereira, Artur; Lau, Nuno; Fernández-Blanco, Enrique (Elsevier, 2023)[Abstract]: Path Planning methods for the autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise due to the numerous advantages they bring. There are increasingly more scenarios where autonomous control ... -
UAV Swarm Path Planning With Reinforcement Learning for Field Prospecting
Puente-Castro, Alejandro; Rivero, Daniel; Pazos, A.; Fernández-Blanco, Enrique (Springer, 2022-03-03)[Abstract] There has been steady growth in the adoption of Unmanned Aerial Vehicle (UAV) swarms by operators due to their time and cost benefits. However, this kind of system faces an important problem, which is the ... -
Using Artificial Neural Networks for Identifying Patients with Mild Cognitive Impairment Associated with Depression Using Neuropsychological Test Features
Mato-Abad, Virginia; Jiménez, Isabel; García-Vázquez, Rafael; Aldrey, José M.; Rivero, Daniel; Cacabelos, Purificación; Andrade-Garda, Javier; Pías-Peleteiro, Juan M.; Rodríguez-Yáñez, Santiago (M D P I AG, 2018-09-12)[Abstract] Depression and cognitive impairment are intimately associated, especially in elderly people. However, the association between late-life depression (LLD) and mild cognitive impairment (MCI) is complex and currently ... -
Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification
Rivero, Daniel; Aguiar-Pulido, Vanessa; Fernández-Blanco, Enrique; Gestal, M. (Inderscience, 2013)[Abstract] ANNs are one of the most successful learning systems. For this reason, many techniques have been published that allow the obtaining of feed-forward networks. However, fe w ... -
Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils
Fernández-Lozano, Carlos; Cedrón, Francisco; Rivero, Daniel; Dorado, Julián; Andrade-Garda, José Manuel; Pazos, A.; Gestal, M. (Emerald, 2016-06)[Abstract] Purpose – The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate ... -
Using Reinforcement Learning in the Path Planning of Swarms of UAVs for the Photographic Capture of Terrains
Puente-Castro, Alejandro; Rivero, Daniel; Pazos, A.; Fernández-Blanco, Enrique (MDPI, 2021)[Abstract] The number of applications using unmanned aerial vehicles (UAVs) is increasing. The use of UAVs in swarms makes many operators see more advantages than the individual use of UAVs, thus reducing operational time ...