Aerial Forest Fire Detection based on Transfer Learning and Improved Faster RCNN
Author:
Affiliation:
1. Beijing University of Technology,Faculty of Information Technology,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10164832/10164812/10165603.pdf?arnumber=10165603
Reference10 articles.
1. Fire Detection and Segmentation using YOLOv5 and U-NET
2. Fire Detection from Images Using Faster R-CNN and Multidimensional Texture Analysis
3. Real-Time Detection of Full-Scale Forest Fire Smoke Based on Deep Convolution Neural Network
4. Fog Computing and Deep CNN Based Efficient Approach to Early Forest Fire Detection with Unmanned Aerial Vehicles
5. Forest Fire Detection Based on Lightweight Yolo
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2. Forest fire monitoring system supported by unmanned aerial vehicles and edge computing: a performance evaluation using petri nets;Cluster Computing;2024-04-29
3. Forest fire surveillance systems: A review of deep learning methods;Heliyon;2024-01
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