Geodesic
Image-Based Object Detection Approaches to be Used
Russian journal of nonlinear dynamics, Tome 18 (2022) no. 5, pp. 787-802

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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. 
@article{ND_2022_18_5_a3,
     author = {A. Ali Deeb and F. Shahhoud},
     title = {Image-Based {Object} {Detection} {Approaches} to be {Used}},
     journal = {Russian journal of nonlinear dynamics},
     pages = {787--802},
     publisher = {mathdoc},
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     number = {5},
     year = {2022},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ND_2022_18_5_a3/}
}
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A. Ali Deeb; F. Shahhoud. Image-Based Object Detection Approaches to be Used. Russian journal of nonlinear dynamics, Tome 18 (2022) no. 5, pp. 787-802. http://geodesic.mathdoc.fr/item/ND_2022_18_5_a3/