Metric learning for image-based flower cultivars identification

• Published in: Plant methods Vol. 17; no. 1; p. 65
• Main Authors: Zhang, Ruisong, Tian, Ye, Zhang, Junmei, Dai, Silan, Hou, Xiaogai, Wang, Jue, Guo, Qi
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 22.06.2021; BioMed Central; BMC
• Subjects: Artificial intelligence; Center loss; Classification; Cultivars; data collection; Datasets; Deep Learning; Embedding; Facial recognition technology; Feature extraction; Feature recognition; Flower cultivars identification; Flowers; Flowers & plants; Genotype & phenotype; Identification; Identification and classification; Image retrieval; Imaging systems; Machine learning; Methods; Metric learning; Neural networks; Performance evaluation; phenotype; Phenotypes; Plant breeding; Target recognition; China; Beijing China

The study of plant phenotype by deep learning has received increased interest in recent years, which impressive progress has been made in the fields of plant breeding. Deep learning extremely relies on a large amount of training data to extract and recognize target features in the field of plant phe...