Devipriya A, Department of Computer Science and Engineering, KPR Institute of Engineering and Technology, India
Brindha D, Department of Electronics and Communication Engineering, Coimbatore Institute of Engineering and Technology, India
Kousalya A, Department of Information Technology, Sri Krishna College of Engineering and Technology, India
Online First : 30 December 2020
Publisher Name : IJAICT India Publications, India.
Print ISBN : 978-81-950008-0-7
Online ISBN : 978-81-950008-1-4
Page :426-429
Abstract
Eye state ID is a sort of basic time-arrangement grouping issue in which it is additionally a problem area in the late exploration. Electroencephalography (EEG) is broadly utilized in a vision state in order to recognize people perception form. Past examination was approved possibility of AI & measurable methodologies of EEG vision state arrangement. This research means to propose novel methodology for EEG vision state distinguishing proof utilizing Gradual Characteristic Learning (GCL) in light of neural organizations. GCL is a novel AI methodology which bit by bit imports and prepares includes individually. Past examinations have confirmed that such a methodology is appropriate for settling various example acknowledgment issues. Nonetheless, in these past works, little examination on GCL zeroed in its application to temporalarrangement issues. Thusly, it is as yet unclear if GCL will be utilized for adapting the temporal-arrangement issues like EEG vision state characterization. Trial brings about this examination shows that, with appropriate element extraction and highlight requesting, GCL cannot just productively adapt to timearrangement order issues, yet additionally display better grouping execution as far as characterization mistake rates in correlation with ordinary and some different methodologies. Vision state classification is performed and discussed with KNN classification and accuracy is enriched finally discussed the vision state classification with ensemble machine learning model.
Keywords
Classification, vision state, EEG, GCL, KNN, Ensemble.
Cite this article
Devipriya A, Brindha D and Kousalya A, “A Survey on Machine Learning Algorithms for Vision State Classification and Prediction Through Electroencephalogram (EEG) Signal”, Innovations in Information and Communication Technology, pp. 426-429, December 2020.
Copyright
© 2020 Devipriya A, Brindha D and Kousalya A. 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.
