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All Journal International Journal of Electrical and Computer Engineering
Ivaturi, Sundara Siva Rao
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Computer Science & IT Electrical & Electronics Engineering

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An efficient object detection by autonomous vehicle using deep learning Kolukula, Nitalaksheswara Rao; Kalapala, Rajendra Prasad; Ivaturi, Sundara Siva Rao; Tammineni, Ravi Kumar; Annavarapu, Mahalakshmi; Pyla, Uma
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4287-4295

Abstract

The automation industries have been developing since the first demonstration in the period 1980 to 2000 it is mainly used on automated driving vehicle. Now a day’s automotive companies, technology companies, government bodies, research institutions and academia, investors and venture capitalists are interested in autonomous vehicles. In this work, object detection on road is proposed, which uses deep learning (DL) algorithms. You only look once (YOLO V3, V4, V5). In this system object detection on the road data set is taken as input and the objects are mainly on-road vehicles, traffic signals, cars, trucks and buses. These inputs are given to the models to predict and detect the objects. The Performance of the proposed system is compared with performance of deep learning algorithms convolution neural network (CNN). The proposed system accuracy greater than 76.5% to 93.3%, mean average precision (Map) and frame per second (FPS) are 0.895 and 43.95%.
Co-Authors Annavarapu, Mahalakshmi Kalapala, Rajendra Prasad Kolukula, Nitalaksheswara Rao Pyla, Uma Tammineni, Ravi Kumar