Pixel level segmentation of early-stage in-bag rice root for its architecture analysis

Author:

Gong Liang,Du Xiaofeng,Zhu Kai,Lin Chenghui,Lin Ke,Wang Tao,Lou Qiaojun,Yuan Zheng,Huang Guoqiang,Liu Chengliang

Funder

The Royal Society

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference29 articles.

1. Andrés, C.K., Nagel, K.A., Klaus, P., Ulrich, S., Achim, W., Hanno, S. J. N. P., 2008. Spatio-temporal quantification of differential growth processes in root growth zones based on a novel combination of image sequence processing and refined concepts describing curvature production. 177(3), 811-821.

2. Regulation of root water uptake under abiotic stress conditions;Aroca;J. Exp. Bot.,2012

3. Barbedo, J. G. A., 2018. Factors influencing the use of deep learning for plant disease recognition 172, 84-91.

4. Learning Deep Representation for Imbalanced Classification;Chen;Computer Vision Pattern Recognition,2016

5. Chen, Y., Zhou, X., 2010. Plant root image processing and analysis based on 2D scanner. IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications.

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