An Experimental Assessment of Deep Learning on Highway Driving

Authors

  • Akash Rane
  • wetambari A. Chiwhane

DOI:

https://doi.org/10.46243/jst.2021.v6.i04.pp31-36

Keywords:

learning, neural networks, autonomous driving, computer vision

Abstract

Many groups have used a different types of deep learning techniques on computer vision in highway drivingscenes.duringthispaper,we'llobservetheexperimentalassessmentofdeeplearning.Computer Vision with deep learning can bring a reasonable and robust, yet a powerful solution to the sector of autonomous driving. To prepare the deep learning for practical applications the neural networks requires the data sets to train for all types of scenarios of driving. We collect the Data sets and train the model with deep learning and computer vision algorithms for recognition of cars and lanes.

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Published

2021-08-16

How to Cite

Rane, A., & A. Chiwhane, wetambari. (2021). An Experimental Assessment of Deep Learning on Highway Driving. Journal of Science & Technology (JST), 6(Special Issue 1), 31–36. https://doi.org/10.46243/jst.2021.v6.i04.pp31-36