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Detection of the autonomous car robot using Yolo
Author(s) -
F.I. Abd-AL Sahib,
Hamed Taher,
Rana Fareed Ghani
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1879/3/032129
Subject(s) - robot , autonomous robot , artificial intelligence , computer science , computer vision , environmental science , mobile robot
One of the important object detection applications in smart transportation systems is vehicle detection. Working on self-driving car robots has become an important experiment in recent years to take advantage of innovations and ideas in real self-driving cars, and the detection of robots by multiple algorithms is the most important phase in this work. To solve the problems of self-driving car robot detection. Such as not recognizing shape. In this paper, via the Yolov2 algorithm, we trained a new model for robots. It was proven with the comparison experiments that the proposed method is successful for robot detection. In addition, the proposed model demonstrated excellent feature extraction ability with network visualization.

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