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5 ta ish

Ish: Early Fire Detection Based on Aerial 360-Degree Sensors, Deep Convolution Neural Networks and Exploitation of Fire Dynamic Textures

  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. Fire Detection and Notification Method in Ship Areas Using Deep Learning and Computer Vision Approaches

    Kuldoshbay Avazov, Muhammad Kafeel Jamil, Bahodir Muminov +2

    MaqolaFire Detection and Safety SystemsSensors202313 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. Advancing Maritime Safety: Early Detection of Ship Fires through Computer Vision, Deep Learning Approaches, and Histogram Equalization Techniques

    Aziza Ergasheva, Farkhod Akhmedov, Akmalbek Abdusalomov +1

    MaqolaFire Detection and Safety SystemsFire202412 iqtibos
    ABI

  5. 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