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Low-frequency components analysis in running speech for the automatic detection of parkinson's disease.

, , , , and . INTERSPEECH, page 100-104. ISCA, (2015)

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Characterization of the Handwriting Skills as a Biomarker for Parkinson Disease., , , , , , , , and . CoRR, (2019)Towards Automatic Wild Animal Monitoring: Identification of Animal Species in Camera-trap Images using Very Deep Convolutional Neural Networks., , and . CoRR, (2016)Perceptual Analysis of Speech Signals from People with Parkinson's Disease., , , and . IWINAC (1), volume 7930 of Lecture Notes in Computer Science, page 201-211. Springer, (2013)Is It Possible to Automatically Identify Who Has Forged My Signature? Approaching to the Identification of a Static Signature Forger., , , , and . Document Analysis Systems, page 175-179. IEEE Computer Society, (2012)Automatic detection of parkinson's disease from words uttered in three different languages., , , , , , and . INTERSPEECH, page 1573-1577. ISCA, (2014)Off-line signature verification based on grey level information using texture features., , , and . Pattern Recognition, 44 (2): 375-385 (2011)Detection of different voice diseases based on the nonlinear characterization of speech signals., , , , , and . Expert Syst. Appl., (2017)Analysis of Speech from People with Parkinson's Disease through Nonlinear Dynamics., , , and . NOLISP, volume 7911 of Lecture Notes in Computer Science, page 112-119. Springer, (2013)Angular Contour Parameterization for Signature Identification., , , , and . EUROCAST, volume 5717 of Lecture Notes in Computer Science, page 358-365. Springer, (2009)Two-threshold energy based fall detection using a triaxial accelerometer., , and . EMBC, page 3101-3104. IEEE, (2016)