Identifying non-thrive trees and predicting wood density from resistograph using temporal convolution network
AbstractDeep learning approaches have been adopted in Forestry research including tree classification and inventory prediction. In this study, we proposed an application of a deep learning approach, Temporal Convolution Network, on sequences of radial resistograph profiles to identify non-thrive tre...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-10-01
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| Series: | Forest Science and Technology |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/21580103.2022.2115561 |