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Chinese Bulletin of Botany >

2025 , Vol. 60 >Issue 1: 74 - 80

DOI: https://doi.org/10.11983/CBB24027

TECHNIQUES AND METHODS

An Artificial Intelligence Model for Identifying Grassland Plants in Northern China

  • Jing Xuan ,
  • Qidi Fu ,
  • Gan Xie ,
  • Kai Xue ,
  • Hairui Luo ,
  • Ze Wei ,
  • Mingyue Zhao ,
  • Liang Zhi ,
  • Huawei Wan ,
  • Jixi Gao ,
  • Min Li
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  • 1Big Data and AI Biodiversity Conservation Research Center, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    2China National Botanical Garden, Beijing 100093, China
    3Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China
†These authors contributed equally to this paper

Received date: 2024-02-23

  Accepted date: 2024-06-21

  Online published: 2024-06-24

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Abstract

A large number of software applications for plant identification based on plant images have been developed in recent years. However, those applications are mostly used for identifying the common species countrywide, and thus cannot meet the needs of identifying region-specific vegetation types. In this study, we developed an artificial intelligence model for identifying the dominant plants in Hulunbeier and Xilinhot grassland in Inner Mongolia, based on the image datasets in the Plant Photo Bank of China. The Top5 accuracy of this model reaches 94.6% in the actual field identification tests. Our model provides a new method for the intelligent identification of the major plant species in a specific area.

Key words： grassland plants; artificial intelligence; image recognition; Hulunbeier; Xilinhot

Cite this article

Jing Xuan , Qidi Fu , Gan Xie , Kai Xue , Hairui Luo , Ze Wei , Mingyue Zhao , Liang Zhi , Huawei Wan , Jixi Gao , Min Li . An Artificial Intelligence Model for Identifying Grassland Plants in Northern China[J]. Chinese Bulletin of Botany, 2025 , 60(1) : 74 -80 . DOI: 10.11983/CBB24027

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