Impact Factor

    Farah Shahhoud


    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.
    Keywords: robot navigation, object detection, embedded systems, YOLO algorithms, R-CNN algorithms, object semantics
    Citation: Ali Deeb A., Shahhoud F.,  Image-Based Object Detection Approaches to be Used in Embedded Systems for Robots Navigation, Rus. J. Nonlin. Dyn., 2022, Vol. 18, no. 5, pp.  787-802

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