Fire Detection for CCTV surveillance system using YOLOv2

버전 1.0.0.1 (14.9 MB) 작성자: Wanbin Song
Fire Detection for CCTV surveillance system using YOLOv2
다운로드 수: 718
업데이트 날짜: 2019/11/26

Demo for CCTV surveillance system using Deep Learning, typically YOLOv2 network training demo.

Key Objective for this demo
- Applying deep learning to Video streams from CCTV
- YOLOv2 deep learning model implemented to detect fire from video stream

Demo development Workflow
- Large dataset access : imagedatastore
- Labeling data : Automatic fire labeling class for image labeler defined using image processing apps, e.g. color thresholder, image segmenter
- Training : YOLOv2 training using feature extraction layers + yolov2 layers
- Deployment : Inference speed acceleration by generating CUDA mex file for real-time prediction

Dataset Used
- Cazzolato, Mirela T., et al. "FiSmo: A Compilation of Datasets from Emergency Situations for Fire and Smoke Analysis." Proceedings of the satellite events (2017).
Copyright 2019 The MathWorks, Inc.

인용 양식

Wanbin Song (2024). Fire Detection for CCTV surveillance system using YOLOv2 (https://github.com/wanbin-song/FireDetectionYOLOv2), GitHub. 검색됨 .

MATLAB 릴리스 호환 정보
개발 환경: R2019a
R2019a 이상 릴리스와 호환
플랫폼 호환성
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

GitHub 디폴트 브랜치를 사용하는 버전은 다운로드할 수 없음

버전 게시됨 릴리스 정보
1.0.0.1

Connected to Github

1.0.0

이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.
이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.