The introduction of fire has been both beneficial and disastrous to the natural world and humanity. Many disastrous fires, both natural and man-made, have occurred throughout history. Numerous lives were lost, along with property and money. Numerous innovations have been made in the areas of fire detection, fire suppression, and alarm systems. All of these methods have advantages and disadvantages that can be improved upon in future fire detection innovations. Recent developments in deep learning technology have allowed for precise advancements in the field of vision. Image recognition, object detection, and categorization are all areas where machine learning techniques are put to use. When it comes to identifying and categorizing images, supervised algorithm have made a significant leap forward. In this paper, the strengths and weaknesses of several models for fire prediction, including Random Forest, the Support Vector Machine using MobilenetV2 architecture is discussed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Forecasting Fire Using MobileNet Architecture


    Contributors:


    Publication date :

    2023-11-22


    Size :

    445697 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    RAILWAY TRACK FAULTS DETECTION BASED ON IMAGE PROCESSING USING MOBILENET

    Z. Ragala / A. Retbi / S. Bennani | DOAJ | 2022

    Free access

    Monitoring image anomaly detection based on lightweight network MobileNet

    Zhou, Qi / Feng, Xiancheng / Bao, Zehao et al. | British Library Conference Proceedings | 2022


    NectarGuard: Enhancing Queen Bee Protection and Monitoring with MobileNet-SSD

    Sailaja, K. L. / Ramesh Kumar, P / Bejawada, Kavya et al. | IEEE | 2024


    Research on Fruit and Vegetable Recognition Method Based on MobileNet-V2

    Yingchao, Wang / Na, Li / Jiangyu, Zhang et al. | IEEE | 2024


    A follow-me algorithm for AR.Drone using MobileNet-SSD and PID control

    Garriga Ferrer, Júlia | BASE | 2018

    Free access