Работы, цитирующие эту работу

Работ: 5

Работа: 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

   СтатьяFire Detection and Safety SystemsSensors2021Цитирований: 18

   ABIABI:AkademIndex/openalex/2026.other.021195

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

   Kuldoshbay Avazov, Muhammad Kafeel Jamil, Bahodir Muminov +2

   СтатьяFire Detection and Safety SystemsSensors2023Цитирований: 13

   ABIABI:AkademIndex/openalex/2026.other.040176

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

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

   СтатьяFire Detection and Safety SystemsSensors2023Цитирований: 12

   ABIABI:AkademIndex/openalex/2023.article.000014

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

   СтатьяFire Detection and Safety SystemsFire2024Цитирований: 12

   ABIABI:AkademIndex/openalex/2026.other.074382

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

   Abror Shavkatovich Buriboev, Хошим Рахманов, Temur Soqiyev +1

   СтатьяFire Detection and Safety SystemsSensors2024Цитирований: 4

   ABIABI:AkademIndex/openalex/2026.other.117369