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Random forest-based approach for physiological functional variable selection for driver's stress level classification.

, , , , and . Stat. Methods Appl., 28 (1): 157-185 (2019)

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Self noise and contrast controlled thinning of gray images., , , and . Pattern Recognit., (2016)Evaluation Protocol of Skeletonization Applied to Grayscale Curvilinear Structures., , , and . DICTA, page 1-6. IEEE, (2015)Random forest-based approach for physiological functional variable selection for driver's stress level classification., , , , and . Stat. Methods Appl., 28 (1): 157-185 (2019)Three-dimensional vascular network projective reconstruction from uncalibrated and non-subtracted x-ray rotational angiography image sequence., , , , and . Medical Imaging: Image Processing, volume 4684 of SPIE Proceedings, SPIE, (2002)High resolution volume quantification of the knee joint space based on a semi-automatic segmentation of computed tomography images., , , , , , and . IWSSIP, page 157-161. IEEE, (2015)Statistical detection of salient points using the Dual Tree M-band Wavelet Transform., , and . EUSIPCO, page 1-5. IEEE, (2008)AffectiveROAD system and database to assess driver's attention., , , , and . SAC, page 800-803. ACM, (2018)Nakagami Markov random field as texture model for ultrasound RF envelope image., and . Comput. Biol. Medicine, 39 (6): 535-544 (2009)Texture Image Analysis for Osteoporosis Detection with Morphological Tools., , , , , and . MICCAI (1), volume 3216 of Lecture Notes in Computer Science, page 87-94. Springer, (2004)New Markov Random Field model based on Nakagami distribution for modeling ultrasound RF envelope., , and . EUSIPCO, page 1-5. IEEE, (2006)