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Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium Orchids
Yingshu Peng, Yuxia Zhou, Li Zhang, Hongyan Fu, Guimei Tang, Guolin Huang, Weidong Li
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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