UGC Approved Journal no 63975(19)

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

Volume 10 Issue 4
April-2023
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2304C75


Registration ID:
514170

Page Number

m573-m579

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Title

FOREST FIRE DETECTION USING DEEP LEARNING

Abstract

A forest fire is an unplanned fire that breaks out in a wilderness setting like a forest or prairie. Forest fires have proven to be a threat to humans and wildlife creatures. Early detection of forest fires will decrease the severity preventing huge loss of ecosystems and its effect on global conditions. The forest fire detection model that is developed can be set up to analyze and process images from security cameras, drones, and satellites. Dataset consisting of various images of forests and surroundings resembling forests is used and the images are classified into two categories: “ fire ” and “ smoke ”. To identify the existence or onset of a forest fire in an image efficiently, a deep-learning model is created and trained. In this study, we propose a forest fire detection system that makes use of YOLOv5 for detection and classification and DenseNet for feature extraction. Further the nearest authorities will soon be informed after the specifics of the incident are known.

Key Words

Machine learning, deep learning, convolutional neural network, forest fire detection, object detection, YOLO, DenseNet

Cite This Article

"FOREST FIRE DETECTION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.m573-m579, April-2023, Available :http://www.jetir.org/papers/JETIR2304C75.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

"FOREST FIRE DETECTION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppm573-m579, April-2023, Available at : http://www.jetir.org/papers/JETIR2304C75.pdf

Publication Details

Published Paper ID: JETIR2304C75
Registration ID: 514170
Published In: Volume 10 | Issue 4 | Year April-2023
DOI (Digital Object Identifier):
Page No: m573-m579
Country: Bengaluru, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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