Listar GI-RNASA - Artigos por autor "Rivero, Daniel"

Mostrando ítems 1-20 de 26

    • 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 ...

    • 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 ...

    • 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, ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Hybrid machine learning techniques in the management of harmful algal blooms impact 

      Molares-Ulloa, Andrés; Rivero, Daniel; Gil Ruiz, Jesús; Fernández-Blanco, Enrique; De-la-Fuente-Valentín, Luis (Elsevier, 2023)
      [Abstract]: 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 filter feeders, they can accumulate ...

    • 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, ...