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Miguel Ferrer

Researcher at University of Las Palmas de Gran Canaria

Publications -  499
Citations -  13116

Miguel Ferrer is an academic researcher from University of Las Palmas de Gran Canaria. The author has contributed to research in topics: Population & Signature (logic). The author has an hindex of 58, co-authored 478 publications receiving 11560 citations. Previous affiliations of Miguel Ferrer include Spanish National Research Council & Ministry of Science and Innovation.

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Characterization of Healthy and Pathological Voice Through Measures Based on Nonlinear Dynamics

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.
Proceedings ArticleDOI

Off-line Handwritten Signature GPDS-960 Corpus

TL;DR: The GPDS-960 corpus, an off-line handwritten signature database which contains 24 genuine signatures and 30 forgeries of 960 individuals, is described and preliminary verification results obtained using the GPDS data are presented.
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Prognostic power of proadrenomedullin in community-acquired pneumonia is independent of aetiology

TL;DR: MR-proADM levels closely correlated with increasing severity scores, and showed an important predictive power for complications and short- and long-term mortality (1 yr), and its addition to PSI and CURB-65 significantly improved their prognostic accuracy.
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Accumulation of heavy metals and As in wetland birds in the area around Doñana National Park affected by the Aznalcollar toxic spill.

TL;DR: There is currently no evidence to suggest that the trace element concentrations measured have reached toxic levels, but Zn and Cu from the spill have entered the food chain of the aquatic birds studied, but Cd, Pb and As have not.
Journal ArticleDOI

Dynamic Signature Verification System Based on One Real Signature.

TL;DR: Experimental results suggest that the system proposed is capable of achieving a similar performance to standard verifiers trained with up to five signature specimens, and a challenging benchmark, assessed with multiple state-of-the-art automatic signature verifiers and multiple databases, proves the robustness of the system.