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Study on a new network for identification of leaf diseases of woody fruit plants

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成果类型:
期刊论文
作者:
Wu, Zhao;Jiang, Feng;Cao, Rui
通讯作者:
Jiang, Feng(jf09mail@126.com)
作者机构:
[Cao, Rui; Jiang, Feng; Wu, Zhao] Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha, Peoples R China.
语种:
英文
关键词:
Deep learning;Image recognition;Learning systems;Losses;Transfer learning;Economic loss;Fruit quality;Leaf disease;Model fusion;Modeling parameters;Network-based;Neural-networks;Plant leaves;Plantings;Transfer learning;Fruits
期刊:
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
ISSN:
1064-1246
年:
2022
卷:
43
期:
4
页码:
4133-4144
基金类别:
This research is partially supported by Hunan Provincial Natural Science Foundation (No: 2021JJ31142).
机构署名:
本校为第一机构
院系归属:
计算机与信息工程学院
摘要:
The rapid and effective identification of leaf diseases of woody fruit plants can help fruit farmers prevent and cure diseases in time to improve fruit quality and minimize economic losses, which is of great significance to fruit planting. In recent years, deep learning has shown its unique advantages in image recognition. This paper proposes a new type of network based on deep learning image recognition method to recognize leaf diseases of woody fruit plants. The network merges the output of the convolutional layer of ResNet101 and VGG19 to im...

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