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

Published: 11 September 2024| Version 1 | DOI: 10.17632/mxtvkt5dcy.1
Contributors:
Yingshu Peng, Yuxia Zhou, Li Zhang, Hongyan Fu, Guimei Tang, Guolin Huang, Weidong Li

Description

The authors dedicated over a year to collecting a cultivar image dataset for Chinese Cymbidium orchids named Orchid2024. This dataset contains over 150,000 images spanning 1,275 different categories, involving visits to 20 cities across 12 provincial administrative regions in China to gather pertinent data. Subsequently, we introduced various visual parameter-efficient fine-tuning (PEFT) methods to expedite model development, achieving the highest top-1 accuracy of 86.14% and top-5 accuracy of 95.44%.

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Institutions

Hunan Academy of Agricultural Sciences

Categories

Image Classification, Flower, Orchid

Funding

National Key Research and Development Program of China

2019YFD1100400

Hunan Provincial Science and Technology Innovation Fund

2023CX95

Hunan Key Laboratory of Germplasm Innovation and Comprehensive Utilization of Ornamental Plant

2022YLHH001

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