ISSN2456-3315
Impact Factor10.57
UGC CAREApproved
Low Cost₹599 / $45
CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques
Authors
Priyadarsini S , Vijipriya.G , Dr. E.S.shamila
Keywords
OCR, EM, CNN, ANN
Abstract
An image recognition model simply detect the probability of an object in an image. In contrast to this, object localization refers to identifying the location of an object in an image. An object localization algorithm will give the coordinates of the location of an object in an image to represent its location of an object with respect to the image. Object detection is one of the domain witnessing great success in computer vision. This paper explains the role of deep learning techniques based on convolutional neural network for object detection. A vision based speed breaker and crack detection for early warning notification will focus on the road region and detecting the speed breaker and crack on the road. The system will warn the drivers to slow down their car by reducing a motor speed when they are approaching the speed breaker. With this system, the driver can slow down their car at the appropriate time. This is achieved with CNN algorithm and it does not need its input to be fixed size. The Expectation-Maximization (EM) algorithm is a way to find maximum-likelihood estimates for model parameters when your data is incomplete, has missing data points, or has unobserved (hidden) latent variables which is used to detect cracks on roads.
Full Paper, Downloads & Preview
How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJRTI — journal style
"A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.4, Issue 5, page no.29 - 33, May-2019, Available :https://ijrti.org/papers/IJRTI1905007.pdf
APA — 7th edition
S, P., Vijipriya.G, & E.S.shamila. (2019). A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques. International Journal for Research Trends and Innovation, 4(5), 29 - 33. https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007
MLA — 9th edition
S, Priyadarsini, et al. "A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques." International Journal for Research Trends and Innovation, vol. 4, no. 5, 2019, pp. 29 - 33, https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007.
Chicago — 17th, bibliography
S, Priyadarsini, Vijipriya.G, and E.S.shamila. "A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques." International Journal for Research Trends and Innovation 4, no. 5 (2019): 29 - 33. https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007.
Harvard — author–date
S, P., Vijipriya.G and E.S.shamila (2019) 'A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques', International Journal for Research Trends and Innovation, 4(5), pp. 29 - 33. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007
IEEE — numbered reference
P. S, Vijipriya.G and E.S.shamila, "A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques," IJRTI, vol. 4, no. 5, pp. 29 - 33, May. 2019.
Vancouver — biomedical
S P, Vijipriya.G, E.S.shamila. A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques. IJRTI. 2019 May;4(5):29 - 33.
AMA — 11th edition
S P, Vijipriya.G, E.S.shamila. A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques. IJRTI. 2019;4(5):29 - 33. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI1905007,
author = {Priyadarsini S and Vijipriya.G and E.S.shamila},
title = {A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques},
journal = {International Journal for Research Trends and Innovation},
volume = {4},
number = {5},
pages = {29 - 33},
year = {2019},
month = {May},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - S, Priyadarsini
AU - Vijipriya.G
AU - E.S.shamila
TI - A Road Safety Approach Towards Object Detection Using Image Processing and Deep Learning Techniques
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 4
IS - 5
PY - 2019
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007
SP - 29
EP - 33
ER -
Issue
Volume 4 Issue 5,
May-2019
Pages : 29 - 33
Other Publication Details
Paper Reg. ID
IJRTI_180835
Published Paper ID
IJRTI1905007
Downloads
205,629
Research Area
Engineering
Country
Tirupur, Tamil Nadu, India
Published
May 2019
Published Paper PDF
https://ijrti.org/papers/IJRTI1905007.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI1905007
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 10.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
UGC CARE Approved Journal — Transparent Peer-reviewed journal aligned with UGC’s 2025 suggestive parameters, with CrossRef DOI registration and Scopus Standard metadata on every published paper.
Licence
© 2019 — Authors hold the copyright of this article.
This work is licensed under a
Creative Commons Attribution 4.0 International License
and The Open Definition.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0),
which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Disclaimer:
The content, data and findings in this article are based on the authors’ research and have been
peer-reviewed for academic purposes only. Readers are advised to verify all information before practical
or commercial use. The journal and its editorial board are not liable for any errors, losses or
consequences arising from its use.
Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
