UGC Approved Journal no 63975(19)

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

Volume 6 Issue 4
April-2019
eISSN: 2349-5162

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

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Published Paper ID:
JETIRBE06026


Registration ID:
206666

Page Number

134-142

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Title

AUTOMATIC DETECTION OF FIRE AND ACCIDENT PIXELS USING TENSORFLOW TECHNOLOGIES

Abstract

In the present scenario human requires security services like hospital, police and fire services. These services mainly depend on the human intervention. Without human interaction these services will not respond automatically. Due to lack of quick human interaction, cost of damage increases. In order to reduce the damage, we co-ordinate these services through Artificial Intelligence. Based on the intensity of the damage, photographs and exact location is sent to the respective departments. In this work, we investigate the automatic detection of fire pixel, accidents, and Illegal threat regions in video imagery within real-time bounds without reliance on temporal scene information. As an addition to previous work in the arena, we deliberate the performance of experimentally defined, reduced complexity deep convolutional neural network (CNN) architectures for this task. Opposed to modern trends in the field, our work demonstrates utmost accuracy for entire image binary fire detection, with maximum accuracy within our super pixel localization framework can be attained, via a network architecture of considerably reduced complexity. We show the relative performance accomplished in contradiction of prior work using standard datasets to demonstrate maximally strong real-time fire pixel, accidents, and Illegal threat region detection.

Key Words

Artificial Intelligence, pixel, convolutional neural network, super pixel localization framework, datasets

Cite This Article

"AUTOMATIC DETECTION OF FIRE AND ACCIDENT PIXELS USING TENSORFLOW TECHNOLOGIES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.134-142, April-2019, Available :http://www.jetir.org/papers/JETIRBE06026.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

"AUTOMATIC DETECTION OF FIRE AND ACCIDENT PIXELS USING TENSORFLOW TECHNOLOGIES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp134-142, April-2019, Available at : http://www.jetir.org/papers/JETIRBE06026.pdf

Publication Details

Published Paper ID: JETIRBE06026
Registration ID: 206666
Published In: Volume 6 | Issue 4 | Year April-2019
DOI (Digital Object Identifier):
Page No: 134-142
Country: -, -, -- .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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