title,doi,url,abstract,journal,publication_year,pmid,arxiv
Driver Emotional Status Recognition Using Artificial Neural Network, https://doi.org/10.32628/IJSRCSEIT, https://ijsrcseit.com/CSEIT1726329, Artificial neural network is one of the fascinating area of study the proposed architecture is performs better feature extraction than earlier proposed Fuzzy logic and SVM algorithms. Day to day the automotive industries are actively supporting research and innovations related to safety issues performance and environment. A driver status assessment system constructed in two different modules: one is for driver fatigue detection based on captured images through Digital cameras. The fatigue is a percentage of eyes closure of the best indicator of fatigue for vision systems. And the second one is driver distraction system by using head facial expressions and body a fusion strategy is to deduce the type's driver distractions. Of course many aspects are there but these two fatigue and distraction are only a fraction of all possible drivers' states of their dramatic impact on traffic safety.The standard databases are used for quantitative evaluation of the current state of the art approach using ANN achieves better accuracy then compared to Fuzzy and SVM. The proposed architecture endorses the efficiency and reliable usage of the work for real world applications., International Journal of Scientific Research in Computer Science Engineering and Information Technology, 2017, CSEIT1726329