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.

Downloads

Download data is not yet available.

References

Prabhod, Kummaragunta Joel. "ANALYZING THE ROLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNIQUES IN IMPROVING PRODUCTION SYSTEMS." Science, Technology and Development 10.7 (2021): 698-707.

Sadhu, Amith Kumar Reddy, and Ashok Kumar Reddy Sadhu. "Fortifying the Frontier: A Critical Examination of Best Practices, Emerging Trends, and Access Management Paradigms in Securing the Expanding Internet of Things (IoT) Network." Journal of Science & Technology 1.1 (2020): 171-195.

Tatineni, Sumanth, and Karthik Allam. "Implementing AI-Enhanced Continuous Testing in DevOps Pipelines: Strategies for Automated Test Generation, Execution, and Analysis." Blockchain Technology and Distributed Systems 2.1 (2022): 46-81.

Pulimamidi, Rahul. "Emerging Technological Trends for Enhancing Healthcare Access in Remote Areas." Journal of Science & Technology 2.4 (2021): 53-62.

Perumalsamy, Jegatheeswari, Chandrashekar Althati, and Lavanya Shanmugam. "Advanced AI and Machine Learning Techniques for Predictive Analytics in Annuity Products: Enhancing Risk Assessment and Pricing Accuracy." Journal of Artificial Intelligence Research 2.2 (2022): 51-82.

Devan, Munivel, Lavanya Shanmugam, and Chandrashekar Althati. "Overcoming Data Migration Challenges to Cloud Using AI and Machine Learning: Techniques, Tools, and Best Practices." Australian Journal of Machine Learning Research & Applications 1.2 (2021): 1-39.

Althati, Chandrashekar, Bhavani Krothapalli, and Bhargav Kumar Konidena. "Machine Learning Solutions for Data Migration to Cloud: Addressing Complexity, Security, and Performance." Australian Journal of Machine Learning Research & Applications 1.2 (2021): 38-79.

Sadhu, Ashok Kumar Reddy, and Amith Kumar Reddy. "A Comparative Analysis of Lightweight Cryptographic Protocols for Enhanced Communication Security in Resource-Constrained Internet of Things (IoT) Environments." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 121-142.

Tatineni, Sumanth, and Venkat Raviteja Boppana. "AI-Powered DevOps and MLOps Frameworks: Enhancing Collaboration, Automation, and Scalability in Machine Learning Pipelines." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 58-88.

Downloads

Published

2021-07-29

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: Sep. 19, 2024. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/86

Similar Articles

1-10 of 55

You may also start an advanced similarity search for this article.