Quantifying Perceptual Uncertainty through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Identifying Candidate Kinematic Markers.

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Bibliographic Details
Title:	Quantifying Perceptual Uncertainty through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Identifying Candidate Kinematic Markers.
Authors:	López Moreno, Alberto Nicolás¹ an.lopezmoreno@ugto.mx, Gomez, Geovanni Hernández¹ geov.hernandez@ugto.mx, López-Villagómez, José Manuel¹ jmlopez@ugto.mx, López-Hernández, Juan Manuel¹ jm.lopezvillagomez@ugto.mx
Source:	International Journal of Combinatorial Optimization Problems & Informatics. 2026, Vol. 17 Issue 5, p138-152. 15p.
Database:	Academic Search Ultimate

Description
ISSN:	20071558
DOI:	10.61467/2007.1558.2026.v17i5.1306