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Fig. 5 | Plant Methods

Fig. 5

From: Data-driven crop growth simulation on time-varying generated images using multi-conditional generative adversarial networks

Fig. 5

Time-varying image generation for GrowliFlower with, in the top row, reference images with an early growth stage as input (cyan frame), in the second row, all day-wise generated predictions, and, in the third row, standard deviation images over ten predictions with different noise input \(\varvec{z}\) and otherwise constant input conditions. The two bottom rows show the quality metrics: learned perceptual image patch similarity (LPIPS), multiscale structural similarity (MS-SSIM), and the projected leaf area difference (\(\Delta \hbox {PLA}\))

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Plant Methods

ISSN: 1746-4811