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Cut-and-Paste Reference:
Guo, Y.H., Y. Zhao, T.A. Rothfus, and A.S. Avalos. 2022. A novel invasive plant detection approach using time series images from unmanned aerial systems based on convolutional and recurrent neural networks. Neural Computing & Applications 34(22):20135-20147. https://doi.org/10.1007/s00521-022-07560-3.
Reference Details:
Reference Number: 40887
Type: Journal Article
Author: Guo, Y.H., Y. Zhao, T.A. Rothfus, and A.S. Avalos
Date (year): 2022
Article Title:A novel invasive plant detection approach using time series images from unmanned aerial systems based on convolutional and recurrent neural networks
Journal Name: Neural Computing & Applications
Volume: 34
Issue: 22
Pages: 20135-20147
URL:
Keywords: invasive plant, unmanned aerial system, convolution neural network, recurrent neural network, Phragmites australis, common reed
DOI: 10.1007/s00521-022-07560-3
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Citation information: U.S. Geological Survey. [2024]. Nonindigenous Aquatic Species Database. Gainesville, Florida. Accessed [11/23/2024].

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