Earticle

초록

영어

Research on fire detection has grown steadily over the last few decades which is the key concern of the research community to prevent the lives of mankind and their property from damages. Several researchers developed video fire detection datasets and proposed different machine learning algorithms for its accurate detection. Therefore, it is very significant for the researchers to understand the relevant datasets in this field that can provide help in terms of results comparison and speed up the research based on the existing datasets instead of creating a new dataset. In this paper, we provide a comprehensive overview of existing fire detection datasets. Firstly, we reviewed seven different fire detection datasets in detail, which can provide helps to new researchers in this field. Secondly, we provided a detailed description of these datasets, and analyzed the shortcomings and suggestions for further fruitful research. This paper is helpful for new researchers to identify possible research gaps and limitations about fire detection datasets.

목차

Abstract
I. INTRODUCTION
II. VIDEO FIRE DETECTION DATASETS
III. DISCUSSION
A. Comparison of Video fire detection dataset
B. Limitations of current datasets
C. Recommendations for future datasets
IV. CONCLUSIONS
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• Yakun Xie [ Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University ]
• Jun Zhu [ Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University ]
• Hikmat Yar [ Sejong University ]
• Tanveer Hussain [ Sejong University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004