ForestResNet: A Deep Learning Algorithm for Forest Image Classification

Due to its large area and rugged terrain, the forest often fails to be detected in time and eventually causes severe losses[1]. Therefore, early detection of forest fires is significant for forest fire protection. The application of deep learning to the classification of smoke and fire in forest ima...

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Vydáno v:Journal of physics. Conference series Ročník 2024; číslo 1; s. 12053 - 12058
Hlavní autoři: Tang, Yongqing, Feng, Hao, Chen, Junyan, Chen, Yuan
Médium: Journal Article
Jazyk:angličtina
Vydáno: IOP Publishing 01.09.2021
ISSN:1742-6588, 1742-6596
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Abstract Due to its large area and rugged terrain, the forest often fails to be detected in time and eventually causes severe losses[1]. Therefore, early detection of forest fires is significant for forest fire protection. The application of deep learning to the classification of smoke and fire in forest images can detect forest conditions more accurately. In this paper, a classification network, named ForestResNet, is proposed to efficiently detect forest conditions, which uses ResNet50[2] as a feature extraction network to achieve rapid and accurate extraction of image feature information. Experimental results show that the proposed network achieves excellent segmentation performance in terms of efficiency and accuracy.
AbstractList Due to its large area and rugged terrain, the forest often fails to be detected in time and eventually causes severe losses[1]. Therefore, early detection of forest fires is significant for forest fire protection. The application of deep learning to the classification of smoke and fire in forest images can detect forest conditions more accurately. In this paper, a classification network, named ForestResNet, is proposed to efficiently detect forest conditions, which uses ResNet50[2] as a feature extraction network to achieve rapid and accurate extraction of image feature information. Experimental results show that the proposed network achieves excellent segmentation performance in terms of efficiency and accuracy.
Author Tang, Yongqing
Feng, Hao
Chen, Junyan
Chen, Yuan
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Snippet Due to its large area and rugged terrain, the forest often fails to be detected in time and eventually causes severe losses[1]. Therefore, early detection of...
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Title ForestResNet: A Deep Learning Algorithm for Forest Image Classification
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