Persona:
Rincón Zamorano, Mariano

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ORCID
0000-0002-0138-4662
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Rincón Zamorano
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Mariano
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2011 - 20192
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Fecha de finalización: 2019 × Fecha de inicio: 2010 ×

Resultados de la búsqueda

Mostrando 1 - 2 de 2
  • Miniatura
    Publicación
    Ontologies for early detection of the Alzheimer Disease and other Neurodegenerative Diseases
    (Springer, 2019) Gómez-Valades Batanero, Alba; Martínez Tomás, Rafael; Rincón Zamorano, Mariano
    Nowadays technologies allow an exponential generation of biomedical data, which must be indexed according to some standard criteria to be useful to the scientific and medical community, being neurology one of the areas in which the standardization is more necessary. Ontologies have been highlighted as one of the best options, with their capability of homogenise information, allowing their integration with other kind of information, and the inference of new information based on the data that is stored. We analyse and compare the approaches taken by different research groups inside the area of the Alzheimer’s disease, and the ontologies they developed with the objective of providing a common framework to standardize information, data recovery or as a part of an expert system. However, to make this approach work the ontologies must be maintained over the time, a critical point which is not been followed by any of the ontologies reviewed.
  • Miniatura
    Publicación
    A block-based model for monitoring of human activity
    (Elsevier, 2011-03) Folgado Zuñiga, Encarnación; Carmona, Enrique J.; Rincón Zamorano, Mariano; Bachiller Mayoral, Margarita
    The study of human activity is applicable to a large number of science and technology fields, such as surveillance, biomechanics or sports applications. This article presents BB6-HM, a block-based human model for real-time monitoring of a large number of visual events and states related to human activity analysis, which can be used as components of a library to describe more complex activities in such important areas as surveillance, for example, luggage at airports, clients’ behaviour in banks and patients in hospitals. BB6-HM is inspired by the proportionality rules commonly used in Visual Arts, i.e., for dividing the human silhouette into six rectangles of the same height. The major advantage of this proposal is that analysis of the human can be easily broken down into regions, so that we can obtain information of activities. The computational load is very low, so it is possible to define a very fast implementation. Finally, this model has been applied to build classifiers for the detection of primitive events and visual attributes using heuristic rules and machine learning techniques.