Plant image recognition with deep learning: A review

文献类型： 外文期刊

第一作者： Chen, Ying

作者： Chen, Ying;Zhang, Zizhao;Wang, Zhen;Liu, Bo;Liu, Conghui;Huang, Cong;Dong, Shuangyu;Pu, Xuejiao;Wan, Fanghao;Qiao, Xi;Qian, Wanqiang;Chen, Ying;Huang, Yiqi;Zhang, Zizhao;Wang, Zhen;Qiao, Xi

作者机构：

关键词： Plant image recognition; Deep learning; Feature extraction; Data acquisition

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.3； 五年影响因子：8.3 ）

ISSN： 0168-1699

年卷期： 2023 年 212 卷

页码：

收录情况： SCI

摘要： Significant advances in the field of digital image processing have been achieved in recent years using deep learning, which has significantly exceeded previous methods. Deep learning allows computers to automatically learn pattern features. Manual extraction of plant image features requires careful engineering and considerable domain expertise, so how to use deep learning technology for plant image identification studies has become a research hotspot. The following three elements are presented in this work: the various neural network structures in plant image recognition and recent research on neural network improvement methods; the way of plant image data collection and processing; three important future development directions. This review summarizes the methods used in the field of plant image recognition in the past five years, providing the latest and most practical ideas for solving problems for researchers in this field.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序