Enrique Fernandez-Blanco

Enrique Fernandez-Blanco
University of A Coruña | UDC · Department of Computer Science & Information Technologies

PhD in Computer Science
Associate Professor at University of A Coruna

About

76
Publications
10,590
Reads
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582
Citations
Introduction
Enrique Fernández-Blanco currently works at the Department of Computer Science, University of A Coruña. Enrique does research in Artificial Intelligence, Artificial Neural Network and Evolutionary Computation in Artificial Life, Natural Science, Engineering and Medicine. His current interests are related with Feature Selection, Signal Processing, Evolutionary Computation and Deep Learning
Additional affiliations
September 2021 - present
University of A Coruña
Position
  • Professor (Associate)
September 2020 - September 2021
University of A Coruña
Position
  • Professor (Associate)
January 2019 - present
University of A Coruña
Position
  • Researcher
Education
January 2011 - September 2011
National Distance Education University
Field of study
  • eHealth and Health Informatics
September 2005 - June 2010
University of A Coruña
Field of study
  • Artificial Intelligence
September 1999 - September 2005
University of A Coruña
Field of study
  • Computer Science

Publications

Publications (76)
Article
Full-text available
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 of cultivated mussels, the opening and closing of the production areas is controlled by a monitoring program. In addition to the closures re...
Article
Full-text available
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 calculation of many optimal paths for each UAV. Solving this problem would allow control of many UAVs without human intervention while saving bat...
Article
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 Programming, the proposed method is deterministic and, consequently, does not require the creation of a population of initial solutions....
Article
Full-text available
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 allows to speed up the flight time and, thus, reducing the operational costs. When combined with Artificial Intelligence (AI) algorithms, a sing...
Article
Full-text available
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 the de facto standard. However, this method presents with problems of slowness and the expensiveness of the chemical-reactive process, whi...
Article
Full-text available
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 technique, a non-destructive technique that analyzes the electromagnetic spectrum in search of waves of a certain length. The aim of this proje...
Article
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 involved. This is why we have tried to develop an architecture that makes the best possible use of the resources available on each machine. The...
Article
Full-text available
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 and costs. The main objective of this work is to design a system that, using Reinforcement Learning (RL) and Artificial Neural Networks (AN...
Preprint
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 dozen of different signals, this particular problem has been mainly tackled by using only the Electroencephalograms presented in those records. On the other hand, the oth...
Preprint
Full-text available
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 an important problem which is the calculation of many optimal paths for each UAV. Solving this problem would allow a to control many UAVs without human intervention at the...
Preprint
Full-text available
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 precise assessment in the diagnosis of AD in the earliest and hardest to detect stages. The main objective of this work is to develop a system that automatically detects the pr...
Preprint
Full-text available
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 during sleep. After its recording, the specialists have to score the different signals according to one of the standard guidelines. This proces...
Preprint
Full-text available
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, even though egg marking is not always required outside the European Union. Other authors have already published works using expensive laboratory equipment in order to dete...
Article
Full-text available
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 areas are based on the toxicity analysis of this bivalve’s meat. Sometimes it is not possible to obtain the necessary data for effective...
Article
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 to the low-quality features extracted by those networks. This paper presents a study focused on the scoring of sleeping EEG signals to measure...
Article
Full-text available
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 space, and using this representation to make predictions of the future note events of the musical piece. This approach was trained with differ...
Article
Full-text available
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. Additionally, the current worldwide use of smartphones makes it particularly easy to get this kind of data from people in a non-intrusive...
Article
Full-text available
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 precise assessment in the diagnosis of AD in the earliest and hardest to detect stages. The main objective of this work is to develop a system that automatically detects the pr...
Article
Full-text available
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 during sleep. After its recording, the specialists have to score the different signals according to one of the standard guidelines. This proces...
Preprint
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 other methods such as Genetic Programming, this method is deterministic, and does not involve the creation of a population of initial solutions. Instead of it, a simple exp...
Article
Full-text available
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 looking for carbon-link interactions. This technology analyzes the electromagnetic spectrum in the band between 700 nm and 2500 nm, a band...
Article
Full-text available
Automatic detection of Alzheimer’s disease is a very active area of research. This is due to its usefulness in starting the protocol to stop the inevitable progression of this neurodegenerative disease. This paper proposes a system for the detection of the disease by means of Deep Learning techniques in magnetic resonance imaging (MRI). As a soluti...
Article
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 its main issues. The use of a validation dataset is a common alternative to prevent overfitting in many Machine Learning (ML) techniques, inc...
Preprint
Full-text available
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: music representation into the latent space, and using this representation to make predictions of the future values of the musical piece. This approach was trained with...
Article
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 always required outside the European Union. Other authors have already published works using expensive laboratory equipment in order to det...
Data
660 spectral curves with wavelengths between 740nm to 1070nm at a spectral resolution of 1 nm were obtained using a handheld SCiO NIR spectrometer. Spectral curves correspond to 22 days of continuous monitoring, with 30 shell intact brown poultry eggs. Eggs were collected from a flock of 20.000 hens of the strain H&N with 49-52 week-old. Hens were...
Article
Full-text available
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 farm on a daily basis over 7 years. Records from a total of 24 flocks, each with approximately 20 000 laying hens, were studied. 3. Other similar...
Article
Full-text available
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 the calibration models of NIR spectra in four different stages in a sugar factory. The models were designed for quality monitoring, par...
Article
Full-text available
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 sector, machine learning algorithms have the potential for early detection and warning of problems, which represents a significant miles...
Article
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, etc., que explican las diferentes alternativas o peculiaridades a la hora de su implementación. La irrupción de .NET Framework, en el ámbito e...
Article
Full-text available
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 for this purpose, Artifical Neural Networks (ANNs) is one of the most suited. One of the main problems in the development of this technique is the slow performance of th...
Article
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 in specific diseases. The complexity of the protein structure hinders the direct association of the signaling activity with the molecular structure. Therefore, the propo...
Article
The nucleotide binding proteins are involved into many important cellular processes such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important research topic. The current study proposes a mixed methodology to obtain the first classification model...
Conference Paper
Full-text available
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 as inputs to the classification system. This requirement can make significant unknown information of the signal be missed by the experts and not be included in the featu...
Article
Full-text available
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, etc., que explican las diferentes alternativas o peculiaridades a la hora de su implementación. La irrupción de .NET Framework, en el ámbito e...
Article
Full-text available
Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated met...
Patent
Full-text available
A method for analysis of 2-D gel images obtained using electrophoresis. More particularly, a molecular block-matching method for establishing the correspondence between protein spots in a diagnostic-test image and protein spots in a reference image. Individual protein spot matching is performed, thereby removing the need for alignment of the entire...
Patent
Full-text available
A method for analysis of 2-D gel images obtained using electrophoresis. More particularly, a molecular block-matching method for establishing the correspondence between protein spots in a diagnostic-test image and protein spots in a reference image. Individual protein spot matching is performed, thereby removing the need for alignment of the entire...
Article
The enzyme regulation proteins are very important due to its involvement in many biological processes that is sustaining the life. The complexity of these proteins, the impossibility to identify direct quantification molecular properties associated with the regulation of enzymatic activities, and the structural diversity of them creates the necessi...
Article
Full-text available
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. Instead of it, GP is able to extract the most relevant features needed for classification. This technique has been applied for the solution of...
Article
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, few works describe techniques for developing recurrent networks. This work uses a genetic algorithm for automatic recurrent ANN development. This system has been applied to solve a we...
Article
Aging and life quality is an important research topic nowadays in areas such as life sciences, chemistry, pharmacology, etc. People live longer, and, thus, they want to spend that extra time with a better quality of life. At this regard, there exists a tiny subset of molecules in nature, named antioxidant proteins, that may influence the aging proc...
Article
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 need of an automatic detection of seizures by using the signals of long-term electroencephalographic (EEG) recordings. Due to the non-statio...
Article
Full-text available
Fast cancer diagnosis represents a real necessity in applied medicine due to the importance of this disease. Thus, theoretical models can help as prediction tools. Graph theory representation is one option because it permits us to numerically describe any real system such as the protein macromolecules by transforming real properties into molecular...
Conference Paper
En este trabajo, los autores han adaptado de manera sencilla el comportamiento de un ADN en un modelo artificial. Dicho modelo tiene como objetivo el ser utilizado para extraer reglas de clasificación para un conjunto de problemas bien conocidos. Esta aproximación ha mostrado en las pruebas un comportamiento similar a las referencias más importante...
Conference Paper
Full-text available
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 Regulatory Network (GRN) model, which has a similar processing information capacity as Boole’s Algebra. This paper also describes how to use it t...
Conference Paper
Full-text available
EEG classification is a research topic that has attracted a lot of interest in recent years, as proven by the large number of papers published. To accomplish this task, a lot of classification systems such as Support Vector Machines (SVMs) or Artificial Neural Networks (ANNs) are used. However, Recurrent Artificial Neural Networks (RANNs) that allo...
Conference Paper
Full-text available
Signal classification is based on the extraction of several features that will be used as inputs of a classifier. The selection of these features is one of the most crucial parts, because they will design the search space, and, therefore, will determine the difficulty of the classification. Usually, these features are selected by using some prior k...
Article
Full-text available
There is a need for the study of complex diseases due to their important impact on our society. One of the solutions involves the theoretical methods which are fast and efficient tools that can lead to the discovery of new active drugs specially designed for these diseases. The Quantitative Structure - Activity Relationship models (QSAR) and the co...
Chapter
Full-text available
The main features of a new theoretical model inside the knowledge area called Artificial Embryogeny are described in this paper. Artificial Embryogeny is a term that identifies any model that uses embryological cells or embryological processes as inspiration. This chapter details the theoretical model and it also presents some its apllication to in...
Conference Paper
Full-text available
Genetic Algorithms (GAs) are a technique that has given good results to those problems that require a search through a complex space of possible solutions. A key point of GAs is the necessity of maintaining the diversity in the population. Without this diversity, the population converges and the search prematurely stops, not being able to reach the...
Chapter
The artificial embryogeny term overlaps all the models that try to adapt cellular properties into artificial models. This chapter presents a new model for artificial embryogeny that mimics the behaviour of biological cells, whose characteristics can be applied to solution of computational problems. The paper contains the theoretical development of...
Chapter
The artificial embryogeny term overlaps all the models that try to adapt cellular properties into artificial models. This chapter presents a new model for artificial embryogeny that mimics the behaviour of biological cells, whose characteristics can be applied to solution of computational problems. The paper contains the theoretical development of...
Conference Paper
Full-text available
This paper proposes a new evolutionary method for generating ANNs. In this method, a simple real-number string is used to codify both architecture and weights of the networks. Therefore, a simple GA can be used to evolve ANNs. One of the most interesting features of the technique presented here is that the networks obtained have been optimised, and...