Image-Based Object Detection Approaches to be Used in Embedded Systems for Robots Navigation
Received 15 September 2022; accepted 10 November 2022; published 28 December 2022
2022, Vol. 18, no. 5, pp. 787-802
Author(s): Ali Deeb A., Shahhoud F.
This paper investigates the problem of object detection for real-time agents’ navigation using
embedded systems. In real-world problems, a compromise between accuracy and speed must be
found. In this paper, we consider a description of the architecture of different object detection
algorithms, such as R-CNN and YOLO, to compare them on different variants of embedded
systems using different datasets. As a result, we provide a trade-off study based on accuracy and
speed for different object detection algorithms to choose the appropriate one depending on the
specific application task.
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