Recent advances in the application of deep learning methods to forestry-Reference-Cited by-同舟云学术

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Recent advances in the application of deep learning methods to forestry

Published:2021-06-26 Issue:5 Volume:55 Page:1171-1202
ISSN:0043-7719
Container-title:Wood Science and Technology
language:en
Short-container-title:Wood Sci Technol

Author:

Wang Yong,Zhang Wei,Gao Rui,Jin Zheng,Wang Xiaohuan

Funder

National Natural Science Foundation of China

Forestry Science and Technology Promotion Project of State Forestry and Grassland Administration of China

General program of Chinese Academy of Forestry

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Plant Science,General Materials Science,Forestry

Link

https://link.springer.com/content/pdf/10.1007/s00226-021-01309-2.pdf

Reference141 articles.

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2. Alipanahi B, Delong A, Weirauch MT, Frey BJ (2015) Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nat Biotechnol 33:831–838. https://doi.org/10.1038/nbt.3300

3. Alipour M, Harris DK (2020) Increasing the robustness of material-specific deep learning models for crack detection across different materials. Eng Struct 206:110157. https://doi.org/10.1016/j.engstruct.2019.110157

4. Alkama R, Cescatti A (2016) Biophysical climate impacts of recent changes in global forest cover. Science 351(6273):600. https://doi.org/10.1126/science.aac8083

5. Apte AP, Iyer A, Thor M, Pandya R, Haq R et al (2020) Library of deep-learning image segmentation and outcomes model-implementations. Phys Medica 73:190–196. https://doi.org/10.1016/j.ejmp.2020.04.011

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