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A Survey of Modern Deep Learning based Object Detection Models

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Abstract

Object Detection is the task of classification and
localization of objects in an image or video. It has gained
prominence in recent years due to its widespread applications.
This article surveys recent developments in deep learning based
object detectors. Concise overview of benchmark datasets and
evaluation metrics used in detection is also provided along with
some of the prominent backbone architectures used in recognition
tasks. It also covers contemporary lightweight classification models used on edge devices. Lastly, we compare the performances
of these architectures on multiple metrics

Citation

Zaidi, S., Ansari, M., Aslam, A., Kanwal, N., Asghar, M., & Lee, B. (2022). A Survey of Modern Deep Learning based Object Detection Models. IET Computer Vision, 1-19. https://doi.org/10.1016/j.dsp.2022.103514

Acceptance Date Apr 24, 2021
Publication Date Jun 30, 2022
Publicly Available Date Dec 31, 2023
Journal IET Computer Vision
Print ISSN 1751-9632
Publisher Institution of Engineering and Technology (IET)
Pages 1-19
DOI https://doi.org/10.1016/j.dsp.2022.103514
Publisher URL https://www.sciencedirect.com/science/article/pii/S1051200422001312?via%3Dihub

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