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Implementation of YOLOv5-based Forest Fire Smoke Monitoring Model with Increased Recognition of Unstructured Objects by Increasing Self-learning data
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- 발행기관
- 국제문화기술진흥원 바로가기
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- 간행물
- International Journal of Advanced Culture Technology(IJACT) KCI 등재 바로가기
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- 통권
- Volume 10 Number 4 (2022.12)바로가기
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- 페이지
- pp.536-546
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A423214
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- A society will lose a lot of something in this field when the forest fire broke out. If a forest fire can be detected in advance, damage caused by the spread of forest fires can be prevented early. So, we studied how to detect forest fires using CCTV currently installed. In this paper, we present a deep learning-based model through efficient image data construction for monitoring forest fire smoke, which is unstructured data, based on the deep learning model YOLOv5. Through this study, we conducted a study to accurately detect forest fire smoke, one of the amorphous objects of various forms, in YOLOv5. In this paper, we introduce a method of self-learning by producing insufficient data on its own to increase accuracy for unstructured object recognition. The method presented in this paper constructs a dataset with a fixed labelling position for images containing objects that can be extracted from the original image, through the original image and a model that learned from it. In addition, by training the deep learning model, the performance(mAP) was improved, and the errors occurred by detecting objects other than the learning object were reduced, compared to the model in which only the original image was learned.
목차
Abstract
1. INTRODUCTION
2. RELATED RESEARCH
2.1 Academic Research
2.2 YOLOv5
2.3 Object Detection Model Performance Evaluation Metrics
3. A MODEL FOR WILDFIRE SMOKE DETECTION
3.1 Configuring Datasets
3.2 Extracting Objects
4. IMPLEMENTATION RESULT
5.CONCLUSION
ACKNOWLEDGEMENT
REFERENCES
키워드
Forest Fires Unstructured Object Deep Learning YOLOv5저자
간행물 정보
발행기관
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- 발행기관명
- 국제문화기술진흥원 [The International Promotion Agency of Culture Technology]
- 설립연도
- 2009
- 분야
- 공학>공학일반
- 소개
- 본 진흥원은 문화기술(Culture Technology) 관련 산·학·연·관으로 구성된 비영리 단체이다. 문화기술(CT)은 정보통신기술(ICT), 문화적 사고 기반의 예술, 인문학, 디자인, 사회과학기술이 접목된 신융합기술(New Convergence Technology, NCT)로 정의한다. 인간의 삶의 질을 향상시키고, 진보된 방향으로 변화시키고, 문화기술 관련 분야의 학술 및 기술의 발전과 진흥에 공헌하기 위하여, 제3조의 필요한 사업을 행함을 그 목적으로 한다.
간행물
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- 간행물명
- International Journal of Advanced Culture Technology(IJACT)
- 간기
- 계간
- pISSN
- 2288-7202
- eISSN
- 2288-7318
- 수록기간
- 2013~2025
- 등재여부
- KCI 등재
- 십진분류
- KDC 600 DDC 700
이 권호 내 다른 논문 / International Journal of Advanced Culture Technology(IJACT) Volume 10 Number 4
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