GinJinn: An object-detection pipeline for feature extraction from herbarium specimens
收藏DataCite Commons2021-05-11 更新2024-07-13 收录
下载链接：
https://data.bgbm.org/dataset/gfbio/0033/1
下载链接
链接失效反馈官方服务：
资源简介：
The collection of morphological data in plant evolutionary, taxonomic and ecological studies based on herbarium material has traditionally been a labor-intensive task. We establish GinJinn as a deep-learning object-detection tool for the automatic recognition and extraction of individual leaves or other structures from herbarium specimens. As an example, GinJinn is applied to herbarium specimens of two species of ox-eye daisies of the genus Leucanthemum Mill., namely the diploid L. vulgare Lam. and the tetraploid L. ircutianum DC.
提供机构：
Botanic Garden and Botanical Museum Berlin
创建时间：
2019-09-27
