Development of neural network committee machines for automatic forest fire detection using lidar

2004 ◽  
Vol 37 (10) ◽  
pp. 2039-2047 ◽  
Author(s):  
Armando M. Fernandes ◽  
Andrei B. Utkin ◽  
Alexander V. Lavrov ◽  
Rui M. Vilar
Keyword(s):  
Neural Network ◽  
Forest Fire ◽  
Fire Detection ◽  
Forest Fire Detection

scholarly journals Forest Fire Detection via Feature Entropy Guided Neural Network

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 128
Author(s):  
Zhenwei Guan ◽  
Feng Min ◽  
Wei He ◽  
Wenhua Fang ◽  
Tao Lu
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Forest Fire ◽  
State Of The Art ◽  
Fire Detection ◽  
High Entropy ◽  
Training Samples ◽  
Feature Information ◽  
Forest Fire Detection ◽  
Entropy Source

Forest fire detection from videos or images is vital to forest firefighting. Most deep learning based approaches rely on converging image loss, which ignores the content from different fire scenes. In fact, complex content of images always has higher entropy. From this perspective, we propose a novel feature entropy guided neural network for forest fire detection, which is used to balance the content complexity of different training samples. Specifically, a larger weight is given to the feature of the sample with a high entropy source when calculating the classification loss. In addition, we also propose a color attention neural network, which mainly consists of several repeated multiple-blocks of color-attention modules (MCM). Each MCM module can extract the color feature information of fire adequately. The experimental results show that the performance of our proposed method outperforms the state-of-the-art methods.

scholarly journals Additive neural network for forest fire detection

2019 ◽  
Vol 14 (4) ◽  
pp. 675-682 ◽  
Author(s):  
Hongyi Pan ◽  
Diaa Badawi ◽  
Xi Zhang ◽  
Ahmet Enis Cetin
Keyword(s):  
Neural Network ◽  
Forest Fire ◽  
Fire Detection ◽  
Forest Fire Detection
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