Detection of Driver Emotion Using Deep Learning

Year : 2023 | Volume : 01 | Issue : 01 | Page : 01-06
By

    Sanket Patil

  1. Sujata Bhande

  2. Ankita Hannure

  3. Akramuddin Ahmed

  1. Student, Department of Computer Science, NBN Sinhgad School of Engineering, Ambegaon, Pune,, Maharashtra, India.
  2. Student, Department of Computer Science, NBN Sinhgad School of Engineering, Ambegaon, Pune,, Maharashtra, India
  3. Student, Department of Computer Science, NBN Sinhgad School of Engineering, Ambegaon, Pune,, Maharashtra, India
  4. Assistant Professor, Department of Computer Science, NBN Sinhgad School of Engineering, Ambegaon, Pune, Maharashtra, India

Abstract

High level Driver-Help Frameworks (ADASs) are utilized for expanding security in the auto space, yet momentum ADASs quite work without considering drivers’ states, e.g., whether she/he is genuinely able to drive. Feelings are a significant way of behaving of people and may emerge in driving circumstances. Uncontrolled feelings can prompt unsafe impacts. To control and decrease the adverse consequence of conduct. In this paper we will distinguish the driver’s conduct. We are going to chip away at five classifications, for example, driver messaging, driver turning, safe driving, talking and other movement. By utilizing a convolutional brain network, we are goin to characterize driver behavior. The convolutional brain network extricates the highlights as well as arranges the classification or conduct. In this paper we are trained model on 100 epochs, and we achieve 92.23% accuracy.

Keywords: Convolutional Neural Network, Deep Learning, Image Processing, Object Classification

[This article belongs to International Journal of Electronics Automation(ijea)]

How to cite this article: Sanket Patil, Sujata Bhande, Ankita Hannure, Akramuddin Ahmed Detection of Driver Emotion Using Deep Learning ijea 2023; 01:01-06
How to cite this URL: Sanket Patil, Sujata Bhande, Ankita Hannure, Akramuddin Ahmed Detection of Driver Emotion Using Deep Learning ijea 2023 {cited 2023 Nov 29};01:01-06. Available from: https://journals.stmjournals.com/ijea/article=2023/view=127497

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Regular Issue Subscription Review Article
Volume 01
Issue 01
Received May 16, 2023
Accepted July 18, 2023
Published November 29, 2023