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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Exploring the landscape: Applications and comparative analysis of object detection algorithms

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  • Exploring the landscape: Applications and comparative analysis of object detection algorithms

Harshita Mathur * and Vaibhav Gupta

Faculty of Computer Science, Lachoo Memorial College of Science and Technology (Autonomous), Jodhpur, Rajasthan, India.
 
Research Article
World Journal of Advanced Research and Reviews, 2024, 24(02), 2157-2163
Article DOI: 10.30574/wjarr.2024.24.2.3584
DOI url: https://doi.org/10.30574/wjarr.2024.24.2.3584
 
Received on 14 October 2024; revised on 21 November 2024; accepted on 23 November 2024
 
The review provides an in-depth overview of object detection algorithms in computer vision, addressing a broad spectrum of methods and techniques. It thoroughly examines key algorithms such as HOG, R-CNN, SSD, and YOLO, highlighting their respective strengths and limitations. By assessing the performance of each algorithm in various scenarios, the review offers insights into their practical applications across diverse fields, such as surveillance, healthcare, and autonomous systems. Additionally, it discusses current challenges faced in object detection, such as balancing speed and accuracy, and outlines potential research directions aimed at enhancing robustness, efficiency, and adaptability in future applications.
 
Computer vision; Deep learning; DPM; HOG; Object detection; R-CNN; SSD; YOLO.
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-3584.pdf

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Harshita Mathur and Vaibhav Gupta. Exploring the landscape: Applications and comparative analysis of object detection algorithms. World Journal of Advanced Research and Reviews, 2024, 24(2), 2157-2163. Article DOI: https://doi.org/10.30574/wjarr.2024.24.2.3584

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