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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