Fire Detection in Ship Engine Rooms Based on Deep Learning

火灾探测 计算机科学 任务(项目管理) 深度学习 特征(语言学) 机舱 特征提取 人工智能 工程类 模拟 汽车工程 建筑工程 系统工程 机械工程 语言学 哲学
作者
Jinting Zhu,Jundong Zhang,Yongkang Wong,Yuequn Ge,Ziwei Zhang,Shihan Zhang
出处
期刊:Sensors [MDPI AG]
卷期号:23 (14): 6552-6552 被引量:7
标识
DOI:10.3390/s23146552
摘要

Ship fires are one of the main factors that endanger the safety of ships; because the ship is far away from land, the fire can be difficult to extinguish and could often cause huge losses. The engine room has many pieces of equipment and is the principal place of fire; however, due to its complex internal environment, it can bring many difficulties to the task of fire detection. The traditional detection methods have their own limitations, but fire detection using deep learning technology has the characteristics of high detection speed and accuracy. In this paper, we improve the YOLOv7-tiny model to enhance its detection performance. Firstly, partial convolution (PConv) and coordinate attention (CA) mechanisms are introduced into the model to improve its detection speed and feature extraction ability. Then, SIoU is used as a loss function to accelerate the model's convergence and improve accuracy. Finally, the experimental results on the dataset of the ship engine room fire made by us shows that the mAP@0.5 of the improved model is increased by 2.6%, and the speed is increased by 10 fps, which can meet the needs of engine room fire detection.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
英俊凡霜发布了新的文献求助20
刚刚
朱大帅完成签到,获得积分10
刚刚
超级瑶瑶发布了新的文献求助10
2秒前
孙行者完成签到,获得积分10
2秒前
英姑应助灵巧的山水采纳,获得10
3秒前
充电宝应助寒冷荧荧采纳,获得10
3秒前
要减肥金针菇完成签到,获得积分10
5秒前
小二郎应助echo采纳,获得10
5秒前
7秒前
Renee应助橙子采纳,获得10
8秒前
NexusExplorer应助清清子采纳,获得10
9秒前
彭于彦祖应助linxgyu采纳,获得30
10秒前
12秒前
12秒前
情怀应助追光少年采纳,获得10
14秒前
16秒前
dpp发布了新的文献求助10
16秒前
17秒前
17秒前
18秒前
我的文献发布了新的文献求助10
19秒前
19秒前
fifteen发布了新的文献求助10
19秒前
聪明飞飞完成签到,获得积分10
19秒前
扶苏发布了新的文献求助10
20秒前
20秒前
dpp完成签到,获得积分20
20秒前
过时的笙完成签到,获得积分10
20秒前
田填填完成签到 ,获得积分10
21秒前
KKK完成签到,获得积分10
21秒前
22秒前
研途顺利完成签到,获得积分20
23秒前
bkagyin应助科研通管家采纳,获得30
23秒前
今后应助科研通管家采纳,获得10
23秒前
23秒前
CodeCraft应助科研通管家采纳,获得10
23秒前
田様应助科研通管家采纳,获得10
23秒前
樱桃猴子应助科研通管家采纳,获得10
23秒前
李健应助科研通管家采纳,获得10
23秒前
搜集达人应助科研通管家采纳,获得10
23秒前
高分求助中
Evolution 10000
ISSN 2159-8274 EISSN 2159-8290 1000
Becoming: An Introduction to Jung's Concept of Individuation 600
Ore genesis in the Zambian Copperbelt with particular reference to the northern sector of the Chambishi basin 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3160857
求助须知:如何正确求助?哪些是违规求助? 2812058
关于积分的说明 7894301
捐赠科研通 2470980
什么是DOI,文献DOI怎么找? 1315808
科研通“疑难数据库(出版商)”最低求助积分说明 631003
版权声明 602068