Analysis of a Backpropagation Neural Network Training Algorithm for EEG-Based Drowsiness Identification-Reference-Cited by-同舟云学术

Analysis of a Backpropagation Neural Network Training Algorithm for EEG-Based Drowsiness Identification

Published:2023-11-15 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
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Author:

Rahmawati Annida¹,Yudono Muchtar Ali Setyo²,Darojatun Aulia¹,Hidayatulloh Papat¹,Simbolon Artha Ivonita¹,Wibowo Jony Winaryo¹,Wicaksana B. Berlian Surya³

Affiliation:

1. Research Center for Smart Mechatronics National Research and Innovation Agency,Bandung,Indonesia

2. Putra University,Electrical Engineering Nusa,Sukabumi,Indonesia

3. Research Center for Telecommunications National Research and Innovation Agency,Bandung,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10366459/10366464/10366759.pdf?arnumber=10366759

Reference35 articles.

1. Driver sleepiness, fatigue, careless behavior and risk of motor vehicle crash and injury: Population based case and control study

2. Sleepiness and the risk of road traffic accidents: A systematic review and meta-analysis of previous studies

3. Fatigue Among Indonesian Commercial Vehicle Drivers: A Study Examining Changes in Subjective Responses and Ocular Indicators

4. EEG Spectral Comparison Between Occipital and Prefrontal Cortices for Early Detection of Driver Drowsiness

5. Factors affecting driver injury severity in fatigue and drowsiness accidents: a data mining framework;Tavakoli;J. Inj. Violence Res.,2022

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