10 resultados para COMPARATIVE RECOGNITION

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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In the past few years, human facial age estimation has drawn a lot of attention in the computer vision and pattern recognition communities because of its important applications in age-based image retrieval, security control and surveillance, biomet- rics, human-computer interaction (HCI) and social robotics. In connection with these investigations, estimating the age of a person from the numerical analysis of his/her face image is a relatively new topic. Also, in problems such as Image Classification the Deep Neural Networks have given the best results in some areas including age estimation. In this work we use three hand-crafted features as well as five deep features that can be obtained from pre-trained deep convolutional neural networks. We do a comparative study of the obtained age estimation results with these features.

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The main aim of this paper is to measure the extent to which part-time work enhances fertility for married or cohabiting women of fertile age. The study covers eleven European countries. The data used are a pool sample of five waves of the European Community Household Panel. Given that we believe that the decisions concerning fertility and labor market status are taken jointly, we carry out a simultaneous estimation approach. Results suggest that policy makers wishing to implement adequate part-time schedules so as to enhance fertility should look at the part-time schedules available in Belgium, Ireland and The Netherlands, which enhance fertility for women who take advantage of this flexibility measure so as to reconcile family and work.

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This project introduces an improvement of the vision capacity of the robot Robotino operating under ROS platform. A method for recognizing object class using binary features has been developed. The proposed method performs a binary classification of the descriptors of each training image to characterize the appearance of the object class. It presents the use of the binary descriptor based on the difference of gray intensity of the pixels in the image. It shows that binary features are suitable to represent object class in spite of the low resolution and the weak information concerning details of the object in the image. It also introduces the use of a boosting method (Adaboost) of feature selection al- lowing to eliminate redundancies and noise in order to improve the performance of the classifier. Finally, a kernel classifier SVM (Support Vector Machine) is trained with the available database and applied for predictions on new images. One possible future work is to establish a visual servo-control that is to say the reac- tion of the robot to the detection of the object.

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En esta tesis de máster se presenta una metodología para el análisis automatizado de las señales del sonar de largo alcance y una aplicación basada en la técnica de reconocimiento óptico de Optical Character Recognition, caracteres (OCR). La primera contribución consiste en el análisis de imágenes de sonar mediante técnicas de procesamiento de imágenes. En este proceso, para cada imagen de sonar se extraen y se analizan las regiones medibles, obteniendo para cada región un conjunto de características. Con la ayuda de los expertos, cada región es identi cada en una clase (atún o no-atún). De este modo, mediante el aprendizaje supervisado se genera la base de datos y, a su vez, se obtiene un modelo de clasi cación. La segunda contribución es una aplicación OCR que reconoce y extrae de las capturas de pantalla de imágenes de sonar, los caracteres alfanuméricos correspondientes a los parámetros de situación (velocidad, rumbo, localización GPS) y la confi guración de sonar (ganancias, inclinación, ancho del haz). El objetivo de este proceso es el de maximizar la e ficiencia en la detección de atún en el Golfo de Vizcaya y dar el primer paso hacia el desarrollo de un índice de abundancia de esta especie, el cual esté basado en el procesamiento automático de las imágenes de sonar grabadas a bordo de la ota pesquera durante su actividad pesquera rutinaria.

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Accurate and fast decoding of speech imagery from electroencephalographic (EEG) data could serve as a basis for a new generation of brain computer interfaces (BCIs), more portable and easier to use. However, decoding of speech imagery from EEG is a hard problem due to many factors. In this paper we focus on the analysis of the classification step of speech imagery decoding for a three-class vowel speech imagery recognition problem. We empirically show that different classification subtasks may require different classifiers for accurately decoding and obtain a classification accuracy that improves the best results previously published. We further investigate the relationship between the classifiers and different sets of features selected by the common spatial patterns method. Our results indicate that further improvement on BCIs based on speech imagery could be achieved by carefully selecting an appropriate combination of classifiers for the subtasks involved.

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Employee-owned businesses have recently enjoyed a resurgence of interest as possible ‘alternatives’ to the somewhat tarnished image of conventional investor-owned capitalist firms. Within the context of global economic crisis, such alternatives seem newly attractive. This is somewhat ironic because, for more than a century, academic literature on employee-owned businesses has been dominated by the ‘degeneration thesis’. This suggested that these businesses tend towards failure – they either fail commercially, or they relinquish their democratic characters. Bucking this trend and offering a beacon - especially in the UK - has been the commercially successful, co-owned enterprise of the John Lewis Partnership (JLP) whose virtues have seemingly been rewarded with favourable and sustainable outcomes. This paper makes comparisons between JLP and its Spanish equivalent Eroski – the supermarket group which is part of the Mondragon cooperatives. The contribution of this paper is to examine in a comparative way how the managers in JLP and Eroski have constructed and accomplished their alternative scenarios. Using longitudinal data and detailed interviews with senior managers in both enterprises it explores the ways in which two large, employee-owned, enterprises reconcile apparently conflicting principles and objectives. The paper thus puts some new flesh on the ‘regeneration thesis’.

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Este póster fue presentado en la Summer School on Evolution en Lisboa (15-19 julio de 2013)