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Open Access

Correction

Correction: FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment

  • Siham Essahraui,
  • Ismail Lamaakal,
  • Yassine Maleh,
  • Khalid El Makkaoui,
  • Mouncef Filali Bouami,
  • Ibrahim Ouahbi,
  • Hela Elmannai,
  • Ahmed A. Abd El-Latif

There are errors in the Acknowledgement statement. The correct Acknowledgement statement is as follows: Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R747), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

There is an error in affiliation 3 for author Hela Elmannai. The correct affiliation 3 is: Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.

Reference

  1. 1. Essahraui S, Lamaakal I, Maleh Y, El Makkaoui K, Bouami MF, Ouahbi I, et al. FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment. PLoS One. 2025;20(11):e0332577. pmid:41191636

Citation: Essahraui S, Lamaakal I, Maleh Y, El Makkaoui K, Bouami MF, Ouahbi I, et al. (2026) Correction: FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment. PLoS One 21(1): e0340596. https://doi.org/10.1371/journal.pone.0340596

Published: January 6, 2026

Copyright: © 2026 Essahraui et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.