Object Detection using Deep Learning

Registration ID: IJNRD_217790

Published ID: IJNRD2404862

DOI: http://doi.one/10.1729/Journal.39210

Naman Joshi , Muskan Arora

object detection, deep learning, convolutional neural network

In recent years, there has been a lot of research focused on the difficult job of object detection in computer vision. Customised features and shallow trainable architectures, which are the foundation of traditional object identification techniques, are prone to performance stagnation. Conversely, deep learning techniques have greater strength and are able to learn deeper, semantic characteristics at a higher level. In addition to reviewing the background of deep learning and convolutional neural networks (CNNs), this study offers an overview of object identification frameworks based on deep learning. Typical general object detection structures, performance-enhancing changes, particular detection tasks, and experimental evaluations are also covered. Lastly, it makes encouraging recommendations for further research. To put it briefly, deep learning is an effective instrument for object detection that can outperform more conventional techniques. I strongly advise engineering students who are interested in object detection to read this paper in order to become more knowledgeable about the most recent methods.

Published Paper   E-Certificate

Naman Joshi & Muskan Arora (April-2024). Object Detection using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), i520-i523. http://doi.one/10.1729/Journal.39210

Volume 9 Issue 4, April-2024

Pages : i520-i523

Paper Reg. ID: IJNRD_217790

Published Paper Id: IJNRD2404862

Downloads: 000121989

Research Area: Computer Science & Technology 

Country: Jaipur, Rajasthan, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404862.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404862

Crossref DOI: http://doi.one/10.1729/Journal.39210

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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