Deep Learning Techniques for Real-time Object Detection in Autonomous Vehicles

Authors

  • Dr. Imene Dahmane Professor of Industrial Engineering, University of Los Andes, Colombia Author

Keywords:

Deep Learning

Abstract

Deep Learning methods have been widely applied to traffic scene for separating different types of object. This technology is also quite interesting not only utilizing in the simultaneous detections of multiple objects in aerial images, but also in the real-time detections of objects in car driving scenes [1]. However, deep neural network object detection methods still have high demands on training data and general powerful machines which can handle the matrix operations efficiently. Therefore, implementing these method on the low resources machines for real-time operation is still really time-consuming and having lower detection rates. The paper aims to make deep neural network based object detection for the real-time purpose by making the use of Single Shot Multi-box Method (SSD) for simultaneoulsy detecting the objects in vehicle driving scenes.

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Published

30-12-2023

How to Cite

[1]
Dr. Imene Dahmane, “Deep Learning Techniques for Real-time Object Detection in Autonomous Vehicles”, J. of Artificial Int. Research and App., vol. 3, no. 2, pp. 1–25, Dec. 2023, Accessed: Nov. 22, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/96

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