4 resultados para López, José Hilario, 1798-1869.

em Repositorio Institucional de la Universidad Pública de Navarra - Espanha


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Este trabajo trata de analizar cómo se produce el proceso de integración de las personas inmigrantes en la sociedad española y navarra, y por lo tanto, también el de sus hijos e hijas en la escuela. Para ello, realizamos un repaso de la evolución de la inmigración en el estado español y en Navarra y de cómo esta ha cambiado la realidad de la sociedad. Para el análisis de la integración, también atenderemos a la respuesta que se ha dado a la diversidad cultural tras la llegada de inmigrantes, comparándola con los diferentes modelos que pueden adoptarse y examinando ejemplos de otros países. Además, atenderemos al punto de vista de las personas inmigrantes. Con el fin de conocer mejor esta perspectiva, en la segunda parte del trabajo realizamos un pequeño estudio preguntando a padres y madres inmigrantes sobre las razones de elegir un modelo lingüístico u otro para sus hijos/as.

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This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

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In the first part of this paper we reviewed the fingerprint classification literature from two different perspectives: the feature extraction and the classifier learning. Aiming at answering the question of which among the reviewed methods would perform better in a real implementation we end up in a discussion which showed the difficulty in answering this question. No previous comparison exists in the literature and comparisons among papers are done with different experimental frameworks. Moreover, the difficulty in implementing published methods was stated due to the lack of details in their description, parameters and the fact that no source code is shared. For this reason, in this paper we will go through a deep experimental study following the proposed double perspective. In order to do so, we have carefully implemented some of the most relevant feature extraction methods according to the explanations found in the corresponding papers and we have tested their performance with different classifiers, including those specific proposals made by the authors. Our aim is to develop an objective experimental study in a common framework, which has not been done before and which can serve as a baseline for future works on the topic. This way, we will not only test their quality, but their reusability by other researchers and will be able to indicate which proposals could be considered for future developments. Furthermore, we will show that combining different feature extraction models in an ensemble can lead to a superior performance, significantly increasing the results obtained by individual models.

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De acuerdo a la normativa de TFEs el repositorio no puede dar acceso a este trabajo. Para consultarlo póngase en contacto con el tutor del trabajo. Puede acceder al resumen del mismo pinchando en el pdf adjunto.