169 citations · 596 across the 17 of their papers we have counts for
17 papers
Enhancing Orthopox Image Classification Using Hybrid Machine Learning and Deep Learning Models
Alejandro Puente-Castro, Enrique Fernandez-Blanco, Daniel Rivero +1
Orthopoxvirus infections must be accurately classified from medical pictures for an easy and early diagnosis and epidemic prevention. The necessity for automated and scalable solut…
Genetic Algorithm Based System for Path Planning with Unmanned Aerial Vehicles Swarms in Cell-Grid Environments
Alejandro Puente-Castro, Enrique Fernandez-Blanco, Daniel Rivero
Path Planning methods for autonomously controlling swarms of unmanned aerial vehicles (UAVs) are gaining momentum due to their operational advantages. An increasing number of scena…
Harmful algal bloom forecasting. A comparison between stream and batch learning
Andres Molares-Ulloa, Elisabet Rocruz, Daniel Rivero +4
Diarrhetic Shellfish Poisoning (DSP) is a global health threat arising from shellfish contaminated with toxins produced by dinoflagellates. The condition, with its widespread incid…
Hybrid Machine Learning techniques in the management of harmful algal blooms impact
Andres Molares-Ulloa, Daniel Rivero, Jesus Gil Ruiz +2
Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filte…
Machine Learning in management of precautionary closures caused by lipophilic biotoxins
Andres Molares-Ulloa, Enrique Fernandez-Blanco, Alejandro Pazos +1
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 Galic…
Q-Learning based system for path planning with unmanned aerial vehicles swarms in obstacle environments
Alejandro Puente-Castro, Daniel Rivero, Eurico Pedrosa +3
Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise because of all the advantages they bring. There are more and more scenarios whe…
Ensemble of Convolution Neural Networks on Heterogeneous Signals for Sleep Stage Scoring
Enrique Fernandez-Blanco, Carlos Fernandez-Lozano, Alejandro Pazos +1
Over the years, several approaches have tried to tackle the problem of performing an automatic scoring of the sleeping stages. Although any polysomnography usually collects over a…
UAV Swarm Path Planning with Reinforcement Learning for Field prospecting
Alejandro Puente-Castro, Daniel Rivero, Alejandro Pazos +1
Unmanned Aerial Vehicle (UAV) swarms adoption shows a steady growth among operators due to the benefits in time and cost arisen from their use. However, this kind of system faces a…
Automatic Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniques
Alejandro Puente-Castro, Enrique Fernandez-Blanco, Alejandro Pazos +1
Early detection is crucial to prevent the progression of Alzheimer's disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precis…
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
Enrique Fernandez-Blanco, Daniel Rivero, Alejandro Pazos
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…
Determination of egg storage time at room temperature using a low-cost NIR spectrometer and machine learning techniques
Julian Coronel-Reyes, Ivan Ramirez-Morales, Enrique Fernandez-Blanco +2
Nowadays, 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, e…
A New Deterministic Technique for Symbolic Regression
Daniel Rivero, Enrique Fernandez-Blanco
This paper describes a new method for Symbolic Regression that allows to find mathematical expressions from a dataset. This method has a strong mathematical basis. As opposed to ot…
Classical Music Prediction and Composition by means of Variational Autoencoders
Daniel Rivero, Enrique Fernandez-Blanco, Alejandro Pazos
This paper proposes a new model for music prediction based on Variational Autoencoders (VAEs). In this work, VAEs are used in a novel way in order to address two different problems…
Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models
Carlos Fernandez-Lozano, Ruben F. Cuinas, Jose A. Seoane +3
Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved…
Classification of Two-channel Signals by Means of Genetic Programming
Daniel Rivero, Enrique Fernandez-Blanco, Julian Dorado +1
Traditionally, signal classification is a process in which previous knowledge of the signals is needed. Human experts decide which features are extracted from the signals, and used…
A Hybrid Evolutionary System for Automated Artificial Neural Networks Generation and Simplification in Biomedical Applications
Enrique Fernandez-Blanco, Daniel Rivero, Marcos Gestal +4
Data mining and data classification over biomedical data are two of the most important research fields in computer science. Among the great diversity of techniques that can be used…
Early warning in egg production curves from commercial hens: A SVM approach
Iván Ramírez Morales, Daniel Rivero Cebrián, Enrique Fernández Blanco +1
Artificial Intelligence allows the improvement of our daily life, for instance, speech and handwritten text recognition, real time translation and weather forecasting are common us…