GinJinn: An object-detection pipeline for feature extraction from herbarium specimens
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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.
创建时间：
2019-09-27
