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Identification of varieties in Camellia oleifera leaf based on deep learning technology

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成果类型:
期刊论文
作者:
Dong, Zhipeng;Yang, Fan;Du, Jiayi;Wang, Kailiang;Lv, Leyan;...
通讯作者:
Long, W
作者机构:
[Dong, Zhipeng; Long, Wei; Long, W; Wang, Kailiang] Chinese Acad Forestry, Res Inst Subtrop Forestry, State key Lab Tree Genet & Breeding, Hangzhou 311400, Zhejiang, Peoples R China.
[Dong, Zhipeng; Du, Jiayi; Yang, Fan] Cent South Univ Forestry & Technol, Coll Comp & Informat Engn, Changsha 410004, Hunan, Peoples R China.
[Lv, Leyan] Zhejiang Tongji Vocat Coll Sci & Technol, Coll Hydraul Engn, Hangzhou 311231, Zhejiang, Peoples R China.
通讯机构:
[Long, W ] C
Chinese Acad Forestry, Res Inst Subtrop Forestry, State key Lab Tree Genet & Breeding, Hangzhou 311400, Zhejiang, Peoples R China.
语种:
英文
关键词:
Camellia oleifera;Varieties identification;Deep learning;RegNetY-4.0GF-CBAM
期刊:
Industrial Crops and Products
ISSN:
0926-6690
年:
2024
卷:
216
页码:
118635
基金类别:
Pioneer and Leading Goose R & D Pro-gram of Zhejiang, China [2021C02038]; Zhejiang Science and Technology Major Program on Agricultural New Variety Breeding, China [2021C02070-2]
机构署名:
本校为其他机构
院系归属:
计算机与信息工程学院
摘要:
Camellia oleifera, a woody oil tree, is widely recognized for its valuable oil. Different cultivars of C.oleifera exhibit distinct growth characteristics, oil content, and oil composition. Therefore, the classification of C.oleifera cultivars can aid in the better utilization of C.oleifera resources and improve yield and quality. However, the identification of cultivars remains challenging due to genetic diversity, similarities in leaf morphology, and the influence of geographical environment, among other factors. Comprehensive cultivar identification methods for studying C.oleifera must be es...

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