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},
volume = {18},
number = {5},
year = {2022},
language = {en},
url = {http://geodesic.mathdoc.fr/item/ND_2022_18_5_a3/}
}
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/