An Efficient Deep Learning Algorithm for Fire and Smoke Detection with Limited Data-Reference-Cited by-同舟云学术

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An Efficient Deep Learning Algorithm for Fire and Smoke Detection with Limited Data

Published:2018 Issue:4 Volume:18 Page:121-128
ISSN:1582-7445
Container-title:Advances in Electrical and Computer Engineering
language:en
Short-container-title:Adv. Electr. Comp. Eng.

Author:

NAMOZOV A.,CHO Y. I.

Publisher

Universitatea Stefan cel Mare din Suceava

Subject

Electrical and Electronic Engineering,General Computer Science

Cited by 65 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A hybrid LBP-CNN with YOLO-v5-based fire and smoke detection model in various environmental conditions for environmental sustainability in smart city;Environmental Science and Pollution Research;2024-01-27

2. Fire and Smoke Detection Using YOLO Through Kafka;Frontier Computing on Industrial Applications Volume 4;2024

3. FAST-AlertNet: Early warning fire-induced collapse of large-span steel truss structures;Engineering Applications of Artificial Intelligence;2023-11

4. Fire and Smoke Segmentation Using Active Learning Methods;Remote Sensing;2023-08-23

5. Real-time Fire Detection for Urban Tunnels Based on Multi-Source Data and Transfer Learning;2023 4th International Symposium on Computer Engineering and Intelligent Communications (ISCEIC);2023-08-18

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