Individual Sick Fir Tree (Abies mariesii) Identification in Insect Infested Forests by Means of UAV Images and Deep Learning

Ha Trang Nguyen; Maximo Larry Lopez Caceres; Koma Moritake; Sarah Kentsch; Hase Shu; Yago Diez

doi:https://doi.org/10.5194/egusphere-egu21-14091

[Back] [Session ITS4.3/NH1]

EGU21-14091

https://doi.org/10.5194/egusphere-egu21-14091

EGU General Assembly 2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Individual Sick Fir Tree (Abies mariesii) Identification in Insect Infested Forests by Means of UAV Images and Deep Learning

Ha Trang Nguyen¹, Maximo Larry Lopez Caceres¹, Koma Moritake², Sarah Kentsch¹, Hase Shu¹, and Yago Diez²

Ha Trang Nguyen et al.

¹Faculty of Agriculture, Yamagata University, Tsuruoka, Japan
²Faculty of Science, Yamagata University, Yamagata, Japan

How to cite: Nguyen, H. T., Lopez Caceres, M. L., Moritake, K., Kentsch, S., Shu, H., and Diez, Y.: Individual Sick Fir Tree (Abies mariesii) Identification in Insect Infested Forests by Means of UAV Images and Deep Learning , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14091, https://doi.org/10.5194/egusphere-egu21-14091, 2021.

This abstract has been withdrawn on 28 Apr 2021.