Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium Orchids

Experimental results demonstrate the complexity of the dataset while highlighting the considerable promise of PEFT methods within flower image classification. We believe that our work not only provides a practical tool for orchid researchers, growers and market participants, but also provides a unique and valuable resource for further exploring fine-grained image classification tasks. The dataset and code are available at https://github.com/pengyingshu/Orchid2024 .

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Publication Details

Journal
Plant Methods
Published
2024-08-13
DOI
https://doi.org/10.1186/s13007-024-01252-w
Citations
2
Primary Topic
Plant and animal studies
Type
article
Field-Weighted Citation Impact
2.06
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article

Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium Orchids

Yüxia Zhou, Li Zhang, Weidong Li, Guolin Huang et al.
2 citations
Plant Methods
Plant and animal studies
2.06
article

Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium Orchids

Yüxia Zhou, Li Zhang, Weidong Li, Guolin Huang, Guimei Tang, Huijie Fu, Yingshu Peng
article en
2 citations

Abstract

Experimental results demonstrate the complexity of the dataset while highlighting the considerable promise of PEFT methods within flower image classification. We believe that our work not only provides a practical tool for orchid researchers, growers and market participants, but also provides a unique and valuable resource for further exploring fine-grained image classification tasks. The dataset and code are available at https://github.com/pengyingshu/Orchid2024 .

Plant MethodsVol. 20(1)
Changsha University (CN), Hunan Academy of Agricultural Sciences (CN)
Zero hunger
Openalex Percentile: Top 12%
Plant and animal studies
2.06
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