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The increase in fire accidents has made fire alarm systems a crucial component of any type of construction¿s necessary accessories. The tragedies that happen most frequently today are fire accidents. Numerous techniques for early fire detection have been suggested in order to lessen the frequency of fire incidents and the damage they cause.Introducing Flamed, a state-of-the-art deep learning model for instant fire and smoke detection. When it comes to spotting possible fire threats, Flamed's Convolutional Neural Networks (CNN)-based technology, which was trained on a substantial Kaggle…mehr

Produktbeschreibung
The increase in fire accidents has made fire alarm systems a crucial component of any type of construction¿s necessary accessories. The tragedies that happen most frequently today are fire accidents. Numerous techniques for early fire detection have been suggested in order to lessen the frequency of fire incidents and the damage they cause.Introducing Flamed, a state-of-the-art deep learning model for instant fire and smoke detection. When it comes to spotting possible fire threats, Flamed's Convolutional Neural Networks (CNN)-based technology, which was trained on a substantial Kaggle dataset, provides unmatched accuracy and speed. Flamed's cutting-edge design and quick processing speed enable it to quickly analyze live video feeds and detect flames and smoke with unmatched accuracy. Flamed is the best option for early fire detection in buildings, monitoring industrial environments, and maintaining public safety. Count on Flamed to deliver accurate and fast notifications to protect people and property from the destructive impacts of fire and smoke.
Autorenporträt
O Dr. Khondekar Lutful Hassan trabalha como professor assistente na Universidade Aliah. Publicou mais de 20 artigos de investigação e dois livros. Os seus interesses de investigação são a aprendizagem automática, a IA, etc.Soubhik Ganguly e Md Raihan Sk concluíram o bacharelato em Informática e Engenharia na Universidade Aliah.