High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning

High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning

Abstract Background Effective soybean seed phenotyping demands large-scale accurate quantities of morphological parameters. The traditional manual acquisition of soybean seed morphological phenotype information is error-prone, and time-consuming, which is not feasible for large-scale collection. The...

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Bibliographic Details
Main Authors: Si Yang, Lihua Zheng, Peng He, Tingting Wu, Shi Sun, Minjuan Wang
Format: Article
Language:English
Published: BMC 2021-05-01
Series:Plant Methods
Subjects:
Seed phenotyping
High throughput
Instance segmentation
Deep learning
Mask R-CNN
Online Access:https://doi.org/10.1186/s13007-021-00749-y

Internet

https://doi.org/10.1186/s13007-021-00749-y

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