research-article

Object Detection using Deep Learning: A Review

Authors:

Sarbjeet SinghAuthors Info & Claims

DSMLAI '21': Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence

Pages 328 - 334

https://doi.org/10.1145/3484824.3484889

Published: 13 January 2022 Publication History

Abstract

Object detection is one of the most critical and challenging tasks in computer vision. It is the process of finding objects belonging to some predefined categories and determining their location in an image or video. This paper reviews deep learning-based object detection models. The paper discusses some benchmark datasets. The performance evaluation of different detectors on different datasets based on mean Average Precision (mAP) is reviewed. Object detection is used in different fields in different forms. Applications of object detection like pedestrian detection, autonomous driving, face detection, etc., are presented. Finally, the future scope is discussed to work on new techniques for object detection.

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Wang YSun TLi SYuan XNi WHossain EVincent Poor H(2023)Adversarial Attacks and Defenses in Machine Learning-Empowered Communication Systems and Networks: A Contemporary SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2023.331949225:4(2245-2298)Online publication date: 26-Sep-2023
https://dl.acm.org/doi/10.1109/COMST.2023.3319492
Nguyen TEichholtzer ADriscoll DSemianiw NCorva DKouzani ANguyen TNguyen D(2023)SAWIT: A small-sized animal wild image dataset with annotationsMultimedia Tools and Applications10.1007/s11042-023-16673-383:11(34083-34108)Online publication date: 25-Sep-2023
https://doi.org/10.1007/s11042-023-16673-3
Liu MLin KHuo WHu LHe Z(2023)Feature enhancement modules applied to a feature pyramid network for object detectionPattern Analysis & Applications10.1007/s10044-023-01152-026:2(617-629)Online publication date: 16-Feb-2023
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Index Terms

Object Detection using Deep Learning: A Review
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition
      2. Computer vision tasks
  2. Machine learning

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Other conferences

DSMLAI '21': Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence

August 2021

415 pages

ISBN:9781450387637

DOI:10.1145/3484824

Editors:
Dharm Singh Jat
Namibia University of Science and Technology
,
Colin Stanley
Namibia University of Science and Technology
,
José Quenum
Namibia University of Science and Technology
,
Nilanjan Dey
JIS University, Kolkata
,
Arpit Jain
Namibia University of Science and Technology

Copyright © 2021 ACM.

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Association for Computing Machinery

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Publication History

Published: 13 January 2022

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Ministry of Electronics and Information technology

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DSMLAI '21'

DSMLAI '21': International Conference on Data Science, Machine Learning and Artificial Intelligence

August 9 - 12, 2021

Windhoek, Namibia

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Cited By

Wang YSun TLi SYuan XNi WHossain EVincent Poor H(2023)Adversarial Attacks and Defenses in Machine Learning-Empowered Communication Systems and Networks: A Contemporary SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2023.331949225:4(2245-2298)Online publication date: 26-Sep-2023
https://dl.acm.org/doi/10.1109/COMST.2023.3319492
Nguyen TEichholtzer ADriscoll DSemianiw NCorva DKouzani ANguyen TNguyen D(2023)SAWIT: A small-sized animal wild image dataset with annotationsMultimedia Tools and Applications10.1007/s11042-023-16673-383:11(34083-34108)Online publication date: 25-Sep-2023
https://doi.org/10.1007/s11042-023-16673-3
Liu MLin KHuo WHu LHe Z(2023)Feature enhancement modules applied to a feature pyramid network for object detectionPattern Analysis & Applications10.1007/s10044-023-01152-026:2(617-629)Online publication date: 16-Feb-2023
https://dl.acm.org/doi/10.1007/s10044-023-01152-0
Luo CZhuo JTang KZou JZuo SCai Y(2022)Contrastive Research on Performance of Face Detection based on Classical and Deep Learning Algorithms2022 International Applied Computational Electromagnetics Society Symposium (ACES-China)10.1109/ACES-China56081.2022.10064747(1-4)Online publication date: 9-Dec-2022
https://doi.org/10.1109/ACES-China56081.2022.10064747

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