Deep learning for image-based large-flowered chrysanthemum cultivar recognition.

ABSTRACT:

Background

Cultivar recognition is a basic work in flower production, research, and commercial application. Chinese large-flowered chrysanthemum (Chrysanthemum × morifolium Ramat.) is miraculous because of its high ornamental value and rich cultural deposits. However, the complicated capitulum structure, various floret types and numerous cultivars hinder chrysanthemum cultivar recognition. Here, we explore how deep learning method can be applied to chrysanthemum cultivar recognition.

Results

We propose deep learning models with two networks VGG16 and ResNet50 to recognize large-flowered chrysanthemum. Dataset A comprising 14,000 images for 103 cultivars, and dataset B comprising 197 images from different years were collected. Dataset A was used to train the net

SUBMITTER: Liu Z 

PROVIDER: S-EPMC6892201 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature