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80 results on '"Lucena, Manuel"'

1. Noise Reduction to Compute Tissue Mineral Density and Trabecular Bone Volume Fraction from Low Resolution QCT

Author

Thomsen, Felix, García, José M. Fuertes, Lucena, Manuel, Pisula, Juan, García, Rodrigo de Luis, Broggrefe, Jan, and Delrieux, Claudio

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose a 3D neural network with specific loss functions for quantitative computed tomography (QCT) noise reduction to compute micro-structural parameters such as tissue mineral density (TMD) and bone volume ratio (BV/TV) with significantly higher accuracy than using no or standard noise reduction filters. The vertebra-phantom study contained high resolution peripheral and clinical CT scans with simulated in vivo CT noise and nine repetitions of three different tube currents (100, 250 and 360 mAs). Five-fold cross validation was performed on 20466 purely spongy pairs of noisy and ground-truth patches. Comparison of training and test errors revealed high robustness against over-fitting. While not showing effects for the assessment of BMD and voxel-wise densities, the filter improved thoroughly the computation of TMD and BV/TV with respect to the unfiltered data. Root-mean-square and accuracy errors of low resolution TMD and BV/TV decreased to less than 17% of the initial values. Furthermore filtered low resolution scans revealed still more TMD- and BV/TV-relevant information than high resolution CT scans, either unfiltered or filtered with two state-of-the-art standard denoising methods. The proposed architecture is threshold and rotational invariant, applicable on a wide range of image resolutions at once, and likely serves for an accurate computation of further micro-structural parameters. Furthermore, it is less prone for over-fitting than neural networks that compute structural parameters directly. In conclusion, the method is potentially important for the diagnosis of osteoporosis and other bone diseases since it allows to assess relevant 3D micro-structural information from standard low exposure CT protocols such as 100 mAs and 120 kVp., Comment: A revised version of this manuscript was accepted for publication in Computerized Medical Imaging and Graphics

Published
2020
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9. Human Action Recognition Using Optical Flow Accumulated Local Histograms

Author

Lucena, Manuel, de la Blanca, Nicolás Pérez, Fuertes, José Manuel, Marín-Jiménez, Manuel Jesús, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Araujo, Helder, editor, Mendonça, Ana Maria, editor, Pinho, Armando J., editor, and Torres, María Inés, editor

Published
2009
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10. Human Motion Characterization Using Spatio-temporal Features

Author

Lucena, Manuel J., Fuertes, José Manuel, Pérez de la Blanca, Nicolás, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Martí, Joan, editor, Benedí, José Miguel, editor, Mendonça, Ana Maria, editor, and Serrat, Joan, editor

Published
2007
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11. Matching Deformable Regions Using Local Histograms of Differential Invariants

Author

Pérez de la Blanca, Nicolás, Fuertes, José M., Lucena, Manuel J., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Marques, Jorge S., editor, Pérez de la Blanca, Nicolás, editor, and Pina, Pedro, editor

Published
2005
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12. Real-Time Tracking Using Multiple Target Models

Author

Lucena, Manuel J., Fuertes, José M., Pérez de la Blanca, Nicolás, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Marques, Jorge S., editor, Pérez de la Blanca, Nicolás, editor, and Pina, Pedro, editor

Published
2005
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15. Kalathos+: Construcción de datasets para la clasificación automática de fragmentos de vasijas cerámicas de torno

Author

Segura, Rafael J., Rueda, Antonio J., Ogáyar, Carlos J., Fuertes, José M., García-Fernández, Ángel L., Lucena, Manuel J., López, Alfonso, Moreno, Isabel, and Molinos, Manuel

Subjects
Applied computing, Arts and humanities, Unsupervised learning and clustering, Computational geometry, +Arts+and+humanities%22">CCS Concepts: Applied computing --> Arts and humanities, +Unsupervised+learning+and+clustering%22">Theory of computation --> Unsupervised learning and clustering, Theory of computation
Abstract

En los últimos años las técnicas de aprendizaje profundo se han convertido en una poderosa alternativa a técnicas clásicas de aprendizaje automático orientadas a tareas de clasificación. Esta tecnología se ha aplicado con gran éxito en diversos campos, si bien es necesaria la existencia de un conjunto de datos etiquetados muy grande para afrontar el entrenamiento de las mismas. En este trabajo se presenta un framework para la generación automática de fragmentos de vasijas de cerámica de torno, convenientemente etiquetados, de manera que permitan el entrenamiento de CNNs para la clasificación de dichos fragmentos, y su posterior utilización en tareas de reconstrucción., Modeling, Rafael J. Segura, Antonio J. Rueda, Carlos J. Ogáyar, José M. Fuertes, Ángel L. García-Fernández, Manuel J. Lucena, Alfonso López, Isabel Moreno, and Manuel Molinos

Published
2022
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24. A Voxel-based Deep Learning Approach for Point Cloud Semantic Segmentation

Author

Díaz-Medina, Miguel, Fuertes-García, José Manuel, Ogayar-Anguita, Carlos Javier, and Lucena, Manuel

Subjects
Machine Learning, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Computer Graphics, Computing methodologies
Abstract

Semantic segmentation has been a research topic in computer vision for decades. This task has become a crucial challenge nowadays due to emergence of new technologies such as autonomous driving. Nonetheless, most existing segmentation methods are not designed for handling the unstructured and irregular nature of 3D point clouds. We propose a voxel-based technique for point cloud data semantic segmentation of 3D point clouds using 3D convolutional neural networks. It uses local voxelizations for learning spatial patterns, and also corrects the imbalance of the data, something very problematic with 3D datasets., Spanish Computer Graphics Conference (CEIG), Short Papers, 73, 76, Miguel Díaz-Medina, José-Manuel Fuertes-García, Carlos-Javier Ogayar-Anguita, and Manuel Lucena, CCS Concepts: Computing methodologies--> Computer Graphics; Machine Learning

Published
2019
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43. Temps d'educació

Author

Barrios Lucena, Manuel

Subjects
educación familiar, infancia, medios de enseñanza, televisión educativa
Abstract

Resumen basado en el de la publicación La televisión no dedica a la programación infantil la atención que, según la opinión generalizada de la sociedad, se merece todo lo que tenga que ver con la infancia, a pesar que está en el mismo espacio físico que el niño, es decir en la residencia familiar. Como territorio marginal, la programación infantil puede ser un terreno abonado para experimentar con proyectos imaginativos que repercutan en la calidad de los programas. Universitat de Barcelona. Biblioteca del Campus de Mundet ; Passeig de la Vall d'Hebron 171; 08035 Barcelona; Tel. +34934021035; Fax +34934021034 ESP

Published
2008

45. Educación y biblioteca : revista de documentación y recursos didácticos

Author

Barrios Lucena, Manuel

Subjects
libros para niños, narración de historias, dibujo, programa de televisión, literatura infantil y juvenil
Abstract

Se explica cómo surge la idea de hacer un programa infantil de televisión sobre libros. El proyecto se materializa en la pantalla de la mano de un artista que va dibujando los personajes y escenarios de una narración, mientras una voz en off relata una historia. Los dibujos se suceden a medida que avanza la narración con el fin de crear intriga en el espectador. Este proceso de creación es similar al de la lectura. Madrid Madrid (Comunidad Autónoma). Servicio de Formación del Profesorado. CRIF Las Acacias; Calle General Ricardos, 179; 28025 Madrid; Tel. +34915250893; Fax +34914660991; SRPPIDE@madrid.org ESP

Published
2007

50. Human Motion Characterization Using Spatio-temporal Features.

Author

Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Rangan, C. Pandu, Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Martí, Joan, Benedí, José Miguel, Mendonça, Ana Maria, Serrat, Joan, and Lucena, Manuel J.

Abstract

Local space-time features can be used to detect and characterize motion events in video. Such features are valid for recognizing motion patterns, by defining a vocabulary of primitive features, and representing each video sequence by means of a histogram, in terms of such vocabulary. In this paper, we propose a supervised vocabulary computation technique which is based on the prior classification of the training events into classes, where each class corresponds to a human action. We will compare the performance of our method with the global approach to show that not only does our method obtain better results but it is also computationally less expensive. [ABSTRACT FROM AUTHOR]

Published
2007
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