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An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks
This work presents a proof-of-concept analyzing RGB images of different growth stages of grapevines with the aim to detect and quantify promising plant organs which are related to yield.
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