Fig. 6From: Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotypingComparison of the mean accuracy rate (\(Q_{{ seg}}\), \(S_{r}\), and \(E_{s}\)). Comparison of different approaches by segmentation quality for ExG, ExGR, CIVE, ACE, K-means, and the proposed method, MFL. The bar indicates the standard deviationsBack to article page