An Artificial Intelligence Model for Identifying Grassland Plants in Northern China

doi:10.11983/CBB24027

Abstract

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

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.

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URL: https://www.chinbullbotany.com/EN/10.11983/CBB24027

https://www.chinbullbotany.com/EN/Y2025/V60/I1/74

Figures/Tables 3

References 16

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