Abstract
The study proposed an application to detect cryptomeria trees which had been damaged by squirrels from an aerial image. Each pixel of the aerial image is classified into damaged tree pixels or healthy pixels by super vector machine (SVM) developed in this paper. The application achieves about 82.24% true positive rate (TPR) in detecting damaged trees and about 1.30% false positive rate (FPR). It is a smart tool for monitoring smart forests.
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References
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Lu, X., Yuan, Y, Fang, J.: JM-Net and cluster-SVM for aerial scene classification. In: 26th International Joint Conference on Artificial Intelligence, pp. 2386–2392. IJCAI Press (2017). https://doi.org/10.24963/ijcai.2017/332
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Lo, C.S., Ho, C.S. (2019). An Application of Detecting Cryptomeria Damage by Squirrels Using Aerial Images. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_19
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DOI: https://doi.org/10.1007/978-981-13-9190-3_19
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