Sorghum segmentation and leaf counting using in silico trained deep neural model
Ian Ostermann,
Bedrich Benes,
Mathieu Gaillard
et al.
Abstract:This paper introduces a novel deep neural model for segmenting and tracking the number of leaves in sorghum plants in phenotyping facilities. Our algorithm inputs a sequence of images of a sorghum plant and outputs the segmented images and the number of leaves. The key novelty of our approach is in training the deep neural model. Manual annotations are tedious, and we have developed a procedural three‐dimensional (3D) sorghum model that provides detailed geometry and texture to generate photorealistic 3D model… Show more
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