Scalable learning for bridging the species gap in image-based plant phenotyping (2020-03-24T00:00:00.000000Z)

TL;DR

This paper investigates the use of synthetic data for leaf instance segmentation and presents UPGen: a Universal Plant Generator for bridging the species gap, which leverages domain randomisation to produce widely distributed data samples and models stochastic biological variation.

Authors

Peyman Moghadam

2 papers

Daniel Ward

1 papers

TL;DR

Authors

References67 items

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Example synthetic plant images generated by the UPGen pipeline. Five column pairs present example RGB images (left column) and the corresponding ground truth per-pixel leaf instance annotations

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