Forest fire image recognition based on convolutional neural network
In order to detect fire automatically, a forest fire image recognition method based on convolutional neural networks is proposed in this paper. There are two main types of fire recognition algorithms. One is based on traditional image processing technology and the other is based on convolutional neu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2019-11-01
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| Series: | Journal of Algorithms & Computational Technology |
| Online Access: | https://doi.org/10.1177/1748302619887689 |
| _version_ | 1818250533473878016 |
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| author | Yuanbin Wang Langfei Dang Jieying Ren |
| author_facet | Yuanbin Wang Langfei Dang Jieying Ren |
| author_sort | Yuanbin Wang |
| collection | DOAJ |
| description | In order to detect fire automatically, a forest fire image recognition method based on convolutional neural networks is proposed in this paper. There are two main types of fire recognition algorithms. One is based on traditional image processing technology and the other is based on convolutional neural network technology. The former is easy to lead in false detection because of blindness and randomness in the stage of feature selection, while for the latter the unprocessed convolutional neural network is applied directly, so that the characteristics learned by the network are not accurate enough, and recognition rate may be affected. In view of these problems, conventional image processing techniques and convolutional neural networks are combined, and an adaptive pooling approach is introduced. The fire flame area can be segmented and the characteristics can be learned by this algorithm ahead. At the same time, the blindness in the traditional feature extraction process is avoided, and the learning of invalid features in the convolutional neural network is also avoided. Experiments show that the convolutional neural network method based on adaptive pooling method has better performance and has higher recognition rate. |
| first_indexed | 2024-12-12T15:53:54Z |
| format | Article |
| id | doaj.art-bb1576eb08f7488384979ae08d22547b |
| institution | Directory Open Access Journal |
| issn | 1748-3026 |
| language | English |
| last_indexed | 2024-12-12T15:53:54Z |
| publishDate | 2019-11-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of Algorithms & Computational Technology |
| spelling | doaj.art-bb1576eb08f7488384979ae08d22547b2022-12-22T00:19:32ZengSAGE PublishingJournal of Algorithms & Computational Technology1748-30262019-11-011310.1177/1748302619887689Forest fire image recognition based on convolutional neural networkYuanbin WangLangfei DangJieying RenIn order to detect fire automatically, a forest fire image recognition method based on convolutional neural networks is proposed in this paper. There are two main types of fire recognition algorithms. One is based on traditional image processing technology and the other is based on convolutional neural network technology. The former is easy to lead in false detection because of blindness and randomness in the stage of feature selection, while for the latter the unprocessed convolutional neural network is applied directly, so that the characteristics learned by the network are not accurate enough, and recognition rate may be affected. In view of these problems, conventional image processing techniques and convolutional neural networks are combined, and an adaptive pooling approach is introduced. The fire flame area can be segmented and the characteristics can be learned by this algorithm ahead. At the same time, the blindness in the traditional feature extraction process is avoided, and the learning of invalid features in the convolutional neural network is also avoided. Experiments show that the convolutional neural network method based on adaptive pooling method has better performance and has higher recognition rate.https://doi.org/10.1177/1748302619887689 |
| spellingShingle | Yuanbin Wang Langfei Dang Jieying Ren Forest fire image recognition based on convolutional neural network Journal of Algorithms & Computational Technology |
| title | Forest fire image recognition based on convolutional neural network |
| title_full | Forest fire image recognition based on convolutional neural network |
| title_fullStr | Forest fire image recognition based on convolutional neural network |
| title_full_unstemmed | Forest fire image recognition based on convolutional neural network |
| title_short | Forest fire image recognition based on convolutional neural network |
| title_sort | forest fire image recognition based on convolutional neural network |
| url | https://doi.org/10.1177/1748302619887689 |
| work_keys_str_mv | AT yuanbinwang forestfireimagerecognitionbasedonconvolutionalneuralnetwork AT langfeidang forestfireimagerecognitionbasedonconvolutionalneuralnetwork AT jieyingren forestfireimagerecognitionbasedonconvolutionalneuralnetwork |