Research on deep learning method recognition and a classification model of grassland grass species based on unmanned aerial vehicle hyperspectral remote sensing-Reference-Cited by-同舟云学术

Research on deep learning method recognition and a classification model of grassland grass species based on unmanned aerial vehicle hyperspectral remote sensing

Published:2022-08-07 Issue:1 Volume:69 Page:3-11
ISSN:1744-6961
Container-title:Grassland Science
language:en
Short-container-title:Grassland Science

Author:

Zhu Xiangbing¹^ORCID,Bi Yuge¹,Du Jianmin¹,Gao Xinchao¹,Zhang Tao¹,Pi Weiqiang¹,Zhang Yanbin¹,Wang Yuan¹,Zhang Haijun¹

Affiliation:

1. Mechanical and Electrical Engineering College Inner Mongolia Agricultural University Hohhot China

Funder

National Natural Science Foundation of China

Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/grs.12379

Reference29 articles.

1. Limited evidence for spatial resource partitioning across temperate grassland biodiversity experiments

2. Plant functional group drives the community structure of saprophytic fungi in a grassland biodiversity experiment

3. He K. M. Zhang X. Y. Ren S. Q. Sun J. &Ieee. (2016).Deep residual learning for image recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 770–778.https://doi.org/10.1109/cvpr.2016.90

4. Grazing intensity significantly changes the C : N : P stoichiometry in grassland ecosystems

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