Object Detection in Images - Recent Advances: Analyzing recent advances in object detection algorithms and architectures for accurately locating objects within images

Authors

  • Dr. Joseph Msabila Associate Professor of Information Systems, University of Nairobi, Kenya Author

Keywords:

Object detection, Image analysis

Abstract

Object detection in images has witnessed significant advancements in recent years, driven by the development of novel algorithms and architectures. This paper provides a comprehensive review of recent advances in object detection, focusing on methods that have improved the accuracy and efficiency of locating objects within images. We discuss key approaches such as single-stage and two-stage detectors, anchor-based and anchor-free methods, and the integration of deep learning with other techniques. Additionally, we highlight challenges and future research directions in object detection to guide further advancements in this field.

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Published

29-07-2021

How to Cite

[1]
Dr. Joseph Msabila, “Object Detection in Images - Recent Advances: Analyzing recent advances in object detection algorithms and architectures for accurately locating objects within images”, Australian Journal of Machine Learning Research & Applications, vol. 2, no. 2, pp. 118–130, Jul. 2021, Accessed: Nov. 07, 2024. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/86

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