Author:
Abd-AL Sahib F.I.,Taher H. B,Ghani R F.
Abstract
Abstract
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.
Subject
General Physics and Astronomy
Reference10 articles.
1. Object detection with discriminatively trained part-based models;Felzenszwalb;IEEE transactions on pattern analysis and machine intelligence,2009
Cited by
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