APA (7th ed.) Citation

López Moreno, A. N., Gomez, G. H., López-Villagómez, J. M., & López-Hernández, J. M. (2026). Quantifying Perceptual Uncertainty through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Identifying Candidate Kinematic Markers. International Journal of Combinatorial Optimization Problems & Informatics, 17(5), 138. https://doi.org/10.61467/2007.1558.2026.v17i5.1306

Chicago Style (17th ed.) Citation

López Moreno, Alberto Nicolás, Geovanni Hernández Gomez, José Manuel López-Villagómez, and Juan Manuel López-Hernández. "Quantifying Perceptual Uncertainty Through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Identifying Candidate Kinematic Markers." International Journal of Combinatorial Optimization Problems & Informatics 17, no. 5 (2026): 138. https://doi.org/10.61467/2007.1558.2026.v17i5.1306.

MLA (9th ed.) Citation

López Moreno, Alberto Nicolás, et al. "Quantifying Perceptual Uncertainty Through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Identifying Candidate Kinematic Markers." International Journal of Combinatorial Optimization Problems & Informatics, vol. 17, no. 5, 2026, p. 138, https://doi.org/10.61467/2007.1558.2026.v17i5.1306.