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7 ta ish

Ish: Automatic fire pixel detection using image processing: a comparative analysis of rule-based and machine learning-based methods

  1. An Improvement of the Fire Detection and Classification Method Using YOLOv3 for Surveillance Systems

    Akmalbek Abdusalomov, Nodirbek Baratov, Alpamis Kutlimuratov +1

    MaqolaFire Detection and Safety SystemsSensors202118 iqtibos
    ABI

  2. An Improved Forest Fire Detection Method Based on the Detectron2 Model and a Deep Learning Approach

    Akmalbek Abdusalomov, Bappy MD Siful Islam, Rashid Nasimov +2

    MaqolaFire Detection and Safety SystemsSensors202314 iqtibos
    ABI

  3. A YOLOv6-Based Improved Fire Detection Approach for Smart City Environments

    Saydirasulov Norkobil Saydirasulovich, Akmalbek Abdusalomov, Muhammad Kafeel Jamil +3

    MaqolaFire Detection and Safety SystemsSensors202312 iqtibos
    ABI

  4. Robust Forest Fire Detection Method for Surveillance Systems Based on You Only Look Once Version 8 and Transfer Learning Approaches

    Nodir Yunusov, Bappy MD Siful Islam, Akmalbek Abdusalomov +1

    MaqolaFire Detection and Safety SystemsProcesses20247 iqtibos
    ABI

  5. Forest Fire Detection and Notification Method Based on AI and IoT Approaches

    Kuldoshbay Avazov, An Eui Hyun, A. S. +3

    MaqolaFire Detection and Safety SystemsFuture Internet20236 iqtibos
    ABI

  6. Improving Fire Detection Accuracy through Enhanced Convolutional Neural Networks and Contour Techniques

    Abror Shavkatovich Buriboev, Хошим Рахманов, Temur Soqiyev +1

    MaqolaFire Detection and Safety SystemsSensors20244 iqtibos
    ABI

  7. Integrating Color and Contour Analysis with Deep Learning for Robust Fire and Smoke Detection

    Abror Shavkatovich Buriboev, Akmal Abduvaitov, Heung Seok Jeon

    MaqolaFire Detection and Safety SystemsSensors20252 iqtibos
    ABI