LiveZilla Live Chat Software

Drowsy Driver Detection using Representation Learning

Drowsy Driver Detection using Representation Learning

Starting at: Rs.4,500.00

4500 reward points

Drowsy Driver Detection using Representation Learning

 The advancement of computing technology over the years has provided assistance to drivers mainly in the form of intelligent vehicle systems. Driver fatigue is a significant factor in a large number of vehicle accidents. Thus, driver drowsiness detection has been considered a major potential area so as to prevent a huge number of sleep induced road accidents. This paper proposes a vision based intelligent algorithm to detect driver drowsiness. Previous approaches are generally based on blink rate, eye closure, yawning, eye brow shape and other hand engineered facial features. The proposed algorithm makes use of features learnt using convolutional neural network so as to explicitly capture various latent facial features and the complex non-linear feature interactions. A softmax layer is used to classify the driver as drowsy or non-drowsy. This system is hence used for warning the driver of drowsiness or in attention to prevent traffic accidents.We present both qualitative and quantitative results to substantiate the claims made in the paper.


ClickMyProject Specifications
Including Packages
  * Supporting Softwares   * 24/7 Support
  * Complete Source Code   * Ticketing System
  * Complete Documentation   * Voice Conference
  * Complete Presentation Slides   * Video On Demand *
  * Flow Diagram   * Remote Connectivity *
  * Database File   * Code Customization **
  * Screenshots   * Document Customization **
  * Execution Procedure   * Live Chat Support
  * Readme File   * Toll Free Support *
  * Addons    
  * Video Tutorials    

*- PremiumSupport Service (Based on Service Hours) ** - Premium Development Service (Based on Requirements)

Add to Cart:

  • Model: PROJ5401
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

Please Choose:


This product was added to our catalog on Monday 19 September, 2016.