人工智能
图像处理
领域(数学)
人工神经网络
深度学习
数字图像处理
机器学习
领域(数学分析)
计算机科学
植物鉴定
模式识别(心理学)
图像(数学)
数学
数学分析
纯数学
作者
Huiling Chen,Yiqi Huang,Zizhao Zhang,Zhen Wang,Lei Zhu,Conghui Liu,Cong Huang,Shuangyu Dong,Xuejiao Pu,Fanghao Wan,Xi Qiao,Wanqiang Qian
标识
DOI:10.1016/j.compag.2023.108072
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.
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