Open Access
Issue
ITM Web Conf.
Volume 44, 2022
International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
Article Number 03030
Number of page(s) 5
Section Computing
DOI https://doi.org/10.1051/itmconf/20224403030
Published online 05 May 2022
  1. Chin-Teng Lin, Ruei-Cheng Wu, Sheng-Fu Liang, Wen-Hung Chao, Yu-Jie Chen and Tzyy Ping Jung, “EEG-based drowsiness estimation for safety driving using independent component analysis,” in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 52, no. 12 pp. 2726–2738, Dec. 2005, doi: 10.1109/TCSI.2005.857555. [CrossRef] [Google Scholar]
  2. Saini, Vandna, and Rekha Saini. “Driver drowsiness detection system and techniques: a review.” International Journal of Computer Science and Information Technologies. [Google Scholar]
  3. Jung T.P., Makeig S., Stensmo M., Sejnowski T.J. Estimating alertness from the EEG power spectrum. IEEE Trans Biomed Eng. 1997 Jan;44(1):60–9. doi: 10.1109/10.553713. PMID: 9214784. [CrossRef] [Google Scholar]
  4. Puri D., Nalbalwar S., Nandgaonkar A., “EEG Based Diagnosis of Alzheimer's Disease Using Kol-mogorov Complexity”, Applied Information Processing Systems. Advances in Intelligent Systems and Computing, vol 1354. Springer, Singapore. https://doi.org/10.1007/978-981-16-2008-9_15. [Google Scholar]
  5. Kehri V., Puri D., Awale R.N., “Entropy-Based Facial Movements Recognition Using CPVM”, Applied Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1155, 2020, Springer, Singapore. https://doi.org/10.1007/97898115402952. [Google Scholar]
  6. Digambar Puri, Sanjay Nalbalwar, Anil Nandgaonkar, Abhay Wagh, “Alzheimer's disease detection from optimal electroencephalogram channels and tunable Q-wavelet transform”, Indonesian Journal of Electrical Engineering and Computer Science, vol. 25, no. 3 pp. 1420–1428, March 2022, ISSN: 2502-4752, DOI: 10.11591/ijeecs.v25.i3.pp1420-1428. [CrossRef] [Google Scholar]
  7. Puri, D., Ingle, R., Kachare, P., Awale, R., “Wavelet Packet Sub-band Based Classification of Alcoholic and Controlled State EEG Signals”, International Conference on Communication and Signal Processing (ICCASP), Atlantis Press, 2016, pp. 562–567, DOI: 10.2991/iccasp.16.2017.82. [Google Scholar]
  8. Chao-Ying Joanne Peng, Kuk Lida Lee, Gary M. Ingersoll “An Introduction to Logistic Regression Analysis and Reporting” (2002) [Google Scholar]
  9. Lin, C.T., Wu, R.C., Jung, T.P. et al. “Estimating Driving Performance Based on EEG Spectrum Analysis”. EURASIP J. Adv. Signal Process. 2005, 521368 (2005). [CrossRef] [Google Scholar]
  10. Hussain, Mahbub, Jordan J. Bird, and Diego R. Faria. “A study on CNN transfer learning for image classification.” UK Workshop on Computational Intelligence. Springer, Cham, (2018). [Google Scholar]
  11. Srivastava, N.; Hinton, G.; Krizhevsky, A.; Sutskever, I.; Salakhutdinov, R. “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”. J. Mach. Learn. Res. (2014). [Google Scholar]
  12. D. Puri, R. Chudiwal, J. Rajput, S. Nalbalwar, A. Nandgaonkar and A. Wagh, “Detection of Alcoholism from EEG signals using Spectral and Tsal- lis Entropy with SVM,” International Conference on Communication information and Computing Technology (ICCICT), 2021, pp. 1–5, doi: 10.1109/IC-CICT50803.2021.9510071. [Google Scholar]

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