YOLO-SF: YOLO for Fire Segmentation Detection-Reference-Cited by-同舟云学术

YOLO-SF: YOLO for Fire Segmentation Detection

Published:2023 Issue: Volume:11 Page:111079-111092
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Cao Xianghong¹^ORCID,Su Yixuan¹^ORCID,Geng Xin¹^ORCID,Wang Yongdong¹

Affiliation:

1. College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou, China

Funder

Science and Technology Research Project of the Henan Province

Research on Key Technologies for Fire Detection Based on Multi-Spectral Image Fusion

Research on Key Technologies of Three-Dimensional Spatial Temperature Field Reconstruction System Under High Temperature and Smoke Environment of Building Fire

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10272581.pdf?arnumber=10272581

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4. Multitasking segmentation of lung and COVID-19 findings in CT scans using modified EfficientDet, UNet and MobileNetV3 models

5. Study on the Situational Awareness System of Mine Fire Rescue Using Faster Ross Girshick-Convolutional Neural Network

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