Unsupervised Domain Adaptation for Forest Fire Recognition Using Transferable Knowledge from Public Datasets
Deep neural networks (DNNs) have driven the recent advances in fire detection. However, existing methods require large-scale labeled samples to train data-hungry networks, which are difficult to collect and even more laborious to label. This paper applies unsupervised domain adaptation (UDA) to tran...
Main Authors: | Zhengjun Yan, Liming Wang, Kui Qin, Feng Zhou, Jineng Ouyang, Teng Wang, Xinguo Hou, Leping Bu |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
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Series: | Forests |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4907/14/1/52 |
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