Výsledky vyhledávání - "Alma Eguizabal"

Source enumeration in the presence of colored noise

Autor: Alma Eguizabal, Christian Lameiro, David Ramirez, Peter J. Schreier

Publikováno v: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
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e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)

In array signal processing, the detection of the number of sources is an important step. Most approaches assume the signals to be embedded in white noise. However, this assumption is unrealistic in many scenarios. In this letter, we propose a strateg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05ddcb89f9c61d694be534caa7f6150e
https://hdl.handle.net/10016/31476

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Deep learning for object detection in fine-art paintings

Autor: Alma Eguizabal, Stanislav Smirnov

Publikováno v: 2018 Metrology for Archaeology and Cultural Heritage (MetroArchaeo).

We propose deep learning and neural networks to automatically detect objects in digital pictures of fine-art paintings. This automatic annotation of digitized artwork provides innovation for content analysis, and therefore enhances the process of doc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::10d1e44ed1d94d98136843b679f7736b
https://doi.org/10.1109/metroarchaeo43810.2018.9089828

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Model-order selection in statistical shape models

Autor: Peter J. Schreier, David Ramirez, Alma Eguizabal

Publikováno v: MLSP
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Statistical shape models enhance machine learning algorithms providing prior information about deformation. A Point Distribution Model (PDM) is a popular landmark-based statistical shape model for segmentation. It requires choosing a model order, whi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b34978061ca9e52e17f54ab1fd67a10
http://arxiv.org/abs/1808.00309

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A weighting strategy for Active Shape Models

Autor: Alma Eguizabal, Peter J. Schreier

Publikováno v: ICIP

Active Shape Models (ASM) are an iterative segmentation technique to find a landmark-based contour of an object. In each iteration, a least-squares fit of a plausible shape to some detected target landmarks is determined. Finding these targets is a c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce191fe94e6a299f646a5df21ad6430e
http://arxiv.org/abs/1707.09233

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Identification of vessel wall anomalies in thoracic aortic aneurysms through optical coherence tomography and gradient-based strategies

Autor: Jose Miguel Lopez-Higuera, Alma Eguizabal, Marta Mayorga, José M. Revuelta, Eusebio Real, J. Fernando Val-Bernal, Olga M. Conde, Alejandro Pontón, Marta Calvo Díez

Publikováno v: Proceedings of SPIE, 2014, Vol. 9129, 912943
Biophotonics: Photonic Solutions for Better Health Care IV 2014, Brussels, 2014
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)

Optical Coherence Tomography is a natural candidate for imaging biological structures just under tissue surface. Human thoracic aorta from aneurysms reveal elastin disorders and smooth muscle cell alterations when visualizing the media layer of the a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5fd26b4a8182daa0eb54129e35196e7d
http://hdl.handle.net/10902/8024

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