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Carlos M. Travieso
Researcher at University of Las Palmas de Gran Canaria
Publications - 241
Citations - 3760
Carlos M. Travieso is an academic researcher from University of Las Palmas de Gran Canaria. The author has contributed to research in topics: Support vector machine & Hidden Markov model. The author has an hindex of 25, co-authored 239 publications receiving 3240 citations. Previous affiliations of Carlos M. Travieso include University of the Basque Country.
Papers
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Offline geometric parameters for automatic signature verification using fixed-point arithmetic
TL;DR: A set of geometric signature features for offline automatic signature verification based on the description of the signature envelope and the interior stroke distribution in polar and Cartesian coordinates are presented.
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Review of Automatic Fault Diagnosis Systems Using Audio and Vibration Signals
TL;DR: A review of recent advances in automatic vibration- and audio-based fault diagnosis in machinery using condition monitoring strategies is provided to provide a review of the most valuable techniques and results.
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Off-line signature verification based on grey level information using texture features
TL;DR: A method for conducting off-line handwritten signature verification works at the global image level and measures the grey level variations in the image using statistical texture features using the co-occurrence matrix and local binary pattern.
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On the selection of non-invasive methods based on speech analysis oriented to automatic Alzheimer disease diagnosis.
Karmele López-de-Ipiña,Jesus-Bernardino Alonso,Carlos M. Travieso,Jordi Solé-Casals,Harkaitz Egiraun,Marcos Faundez-Zanuy,Aitzol Ezeiza,Nora Barroso,Miriam Ecay-Torres,Pablo Martinez-Lage,Unai Martinez de Lizardui +10 more
TL;DR: Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects) and results were very satisfactory and promising for early diagnosis and classification of AD patients.
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Characterization of Healthy and Pathological Voice Through Measures Based on Nonlinear Dynamics
Patricia Henríquez,Jesús B. Alonso,Miguel Ferrer,Carlos M. Travieso,Juan Ignacio Godino-Llorente,Fernando Diaz-de-Maria +5 more
TL;DR: The usefulness of six nonlinear chaotic measures based on nonlinear dynamics theory in the discrimination between two levels of voice quality: healthy and pathological is studied.