Skip to main content

Table 3 Performance when training and testing on different datasets.

From: The use of plant models in deep learning: an application to leaf counting in rosette plants

Training data

Testing data

AbsCountDiff

CountDiff

MSE

\(R^2\)

Agreement (%)

Ara2013-Canon

Ara2012

5.45 (2.04)

\(-\) 5.45 (2.04)

33.9

\(-\) 4.79

0

Ara2012

Ara2013-Canon

5.39 (1.99)

5.39 (1.99)

33.13

\(-\) 6.15

0

S12

Ara2012

1.38 (1.03)

\(-\) 0.25 (1.7)

2.97

0.42

22

S12

Ara2013-Canon

1.82 (1.38)

0.46 (2.24)

5.25

\(-\) 0.33

20

  1. Training on a single dataset of synthetic rosettes performs significantly better than training on a dataset of real rosettes with a different distribution of phenotypes