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Automatic Differentiation of Damaged and Unharmed Grapes Using RGB Images and Convolutional Neural Networks., , , , , , , , и . ECCV Workshops (6), том 12540 из Lecture Notes in Computer Science, стр. 347-359. Springer, (2020)Behind the leaves - Estimation of occluded grapevine berries with conditional generative adversarial networks., , , , , и . CoRR, (2021)Behind the Leaves: Estimation of Occluded Grapevine Berries With Conditional Generative Adversarial Networks., , , , , и . Frontiers Artif. Intell., (2022)Determination of Sugars and Acids in Grape Must Using Miniaturized Near-Infrared Spectroscopy., , , , , , , и . Sensors, 23 (11): 5287 (2023)SmartSpectrometer - Embedded Optical Spectroscopy for Applications in Agriculture and Industry., , , , , , , , , и . Sensors, 21 (13): 4476 (2021)Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks., , , , , и . CoRR, (2020)An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks., , , , , и . CoRR, (2018)Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks., , , , , , и . CVPR Workshops, стр. 2571-2579. Computer Vision Foundation / IEEE, (2019)