Object Detection Using MobileNet-SSD

Registration ID: IJNRD_225397

Published ID: IJNRD2407327

DOI: Click Here to Get

Rajnandini D. Chaudhari

Computer Vision, Object Detection, MobileNet-SSD, Opencv, Single Shot Multi-Box Detector

Object detection remains a cornerstone of computer vision applications, with recent advancements focusing on achieving real-time performance on mobile devices. MobileNet SSD (Single Shot MultiBox Detector) represents a pivotal development in this realm, combining the efficiency of MobileNets with the accuracy of SSD to enable robust object detection in resource-constrained environments. This review paper provides a detailed exploration of the MobileNet SSD architecture, beginning with an in-depth analysis of its key components, including depthwise separable convolutions and feature pyramid networks. These innovations facilitate a lightweight yet effective framework capable of detecting objects across various scales and categories. We survey the evolution of MobileNet SSD from its inception to recent iterations, examining enhancements in model design, training strategies, and deployment optimizations. Additionally, we present comprehensive performance benchmarks and comparisons with alternative object detection approaches, highlighting MobileNet SSD's strengths in terms of speed, accuracy, and computational efficiency. Practical applications of MobileNet SSD in domains such as surveillance, robotics, and augmented reality are discussed, emphasizing its versatility and adaptability to diverse deployment scenarios. Finally, we outline future research directions aimed at further advancing the capabilities and applicability of MobileNet SSD in addressing emerging challenges in real- time object detection.

Published Paper   E-Certificate

Rajnandini D. Chaudhari (July-2024). Object Detection Using MobileNet-SSD. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), d451-d456. https://ijnrd.org/papers/IJNRD2407327.pdf

Volume 9 Issue 7, July-2024

Pages : d451-d456

Paper Reg. ID: IJNRD_225397

Published Paper Id: IJNRD2407327

Downloads: 000121982

Research Area: Computer Engineering 

Country: Jalgaon, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2407327.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407327

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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