Species identification through deep learning and geometrical morphology in oaks (Quercus spp.): Pros and cons.

ABSTRACT: Plant phenotypic characteristics, especially leaf morphology of leaves, are an important indicator for species identification. However, leaf shape can be extraordinarily complex in some species, such as oaks. The great variation in leaf morphology and difficulty of species identification in oaks have attracted the attention of scientists since Charles Darwin. Recent advances in discrimination technology have provided opportunities to understand leaf morphology variation in oaks. Here, we aimed to compare the accuracy and efficiency of species identification in two closely related deciduous oaks by geometric morphometric method (GMM) and deep learning using preliminary identification of simple sequence repeats (nSSRs) as a prior. A total of 538 Asian deciduous oak trees, 16 Q. ali

SUBMITTER: Qi M 

PROVIDER: S-EPMC10864717 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature