Cite
Identification of Logged and Windthrow Areas from Sentinel-2 Satellite Images Using the U-Net Convolutional Neural Network and Factors Affecting Its Accuracy.
MLA
Kanev, A. I., et al. “Identification of Logged and Windthrow Areas from Sentinel-2 Satellite Images Using the U-Net Convolutional Neural Network and Factors Affecting Its Accuracy.” Cosmic Research, vol. 61, Dec. 2023, pp. S152–62. EBSCOhost, https://doi.org/10.1134/S0010952523700569.
APA
Kanev, A. I., Tarasov, A. V., Shikhov, A. N., Podoprigorova, N. S., & Safonov, F. A. (2023). Identification of Logged and Windthrow Areas from Sentinel-2 Satellite Images Using the U-Net Convolutional Neural Network and Factors Affecting Its Accuracy. Cosmic Research, 61, S152–S162. https://doi.org/10.1134/S0010952523700569
Chicago
Kanev, A. I., A. V. Tarasov, A. N. Shikhov, N. S. Podoprigorova, and F. A. Safonov. 2023. “Identification of Logged and Windthrow Areas from Sentinel-2 Satellite Images Using the U-Net Convolutional Neural Network and Factors Affecting Its Accuracy.” Cosmic Research 61 (December): S152–62. doi:10.1134/S0010952523700569.