UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2305A95


Registration ID:
517280

Page Number

k673-k679

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Title

OBJECT DETECTION APPLICATION USING DEEP LEARNING

Abstract

Object detection is a critical task in the field of Artificial Intelligence, Machine Learning, Deep Learning and computer vision with a wide range of applications such as tracking activity inside and outside a store or home, contact-less checkout, inventory management, video analytics among many other things. Convolutional neural networks (CNNs) are a strong tool that deep learning has developed as a way to use to detect objects with cutting-edge performance. In this study, we thoroughly analyze deep learning-based object detection. We address well-known CNN-based object identification algorithms including R-CNN, Fast R-CNN, and Faster R-CNN in addition to more contemporary methods like Single Shot MultiBox Detector (SSD), and You Only Look Once (YOLO). We also talk about the effects of object detection in physical-world applications, such as object recognition for automated driving and object detection for surveillance equipment. We conclude outline several potentials for deep learning-based object detection research, including interpretability, robustness to occlusion and environmental changes, and real-time object detection in resource-constrained situations.

Key Words

SSD, YOLO, Recognition, Detection, CNN

Cite This Article

"OBJECT DETECTION APPLICATION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.k673-k679, May-2023, Available :http://www.jetir.org/papers/JETIR2305A95.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"OBJECT DETECTION APPLICATION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppk673-k679, May-2023, Available at : http://www.jetir.org/papers/JETIR2305A95.pdf

Publication Details

Published Paper ID: JETIR2305A95
Registration ID: 517280
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: k673-k679
Country: RAIPUR, CHHATTISGARH, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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