A Bayesian framework for joint structure and colour based pixel-wise classification of grapevine proximal images

Author:

Abdelghafour F.,Rosu R.,Keresztes B.,Germain C.,Da Costa J.P.

Funder

European Union’s Horizon 2020

French National Institute for Agricultural Research

French National Institute of Vines and Wine

Publisher

Elsevier BV

Subject

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

Reference28 articles.

1. Potential of on-board colour imaging for in-field detection and counting of grape bunches at early fruiting stages;Abdelghafour;Adv. Animal Biosci.,2017

2. Abdelghafour, F., Rosu, R., Keresztes, B., Germain, C., Da Costa, J.-P., 2018. Joint structure and colour based parametric classification of grapevine organs from proximal images through several critical phenological stages. In: 14th Int. Conf. on Precision Agriculture, June 24–June 27, 2018 Montreal, Canada.

3. Log-Euclidean metrics for fast and simple calculus on diffusion tensors;Arsigny;Magn. Reson. Med.,2006

4. Geometric means in a novel vector spacestructure on symmetric positive-de?nite matrices;Arsigny;SIAM J. Matrix Anal. Appl.,2007

5. On the statistical analysis of dirty pictures;Besag;J. Roy. Stat. Soc. Ser. B,1986

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