Data synthesis methods for semantic segmentation in agriculture: A Capsicum annuum dataset

Data synthesis methods for semantic segmentation in agriculture: A Capsicum annuum dataset •This paper proposes a novel methodology to generate synthetic data in agriculture.•Based on empirical measurements, a 3D plant model was created.•Randomised plants were generated with this model and rendered in realistic scenes.•A synthetic dataset was created with a corresponding annotated empirical dataset.•Deep learning models were trained on the datasets and show performance gain. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computers and Electronics in Agriculture Elsevier

Data synthesis methods for semantic segmentation in agriculture: A Capsicum annuum dataset

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Publisher
Elsevier
Copyright
Copyright © 2017 The Authors
ISSN
0168-1699
eISSN
1872-7107
D.O.I.
10.1016/j.compag.2017.12.001
Publisher site
See Article on Publisher Site

Abstract

•This paper proposes a novel methodology to generate synthetic data in agriculture.•Based on empirical measurements, a 3D plant model was created.•Randomised plants were generated with this model and rendered in realistic scenes.•A synthetic dataset was created with a corresponding annotated empirical dataset.•Deep learning models were trained on the datasets and show performance gain.

Journal

Computers and Electronics in AgricultureElsevier

Published: Jan 1, 2018

References

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