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Estimating Crop Seed Composition Using Machine Learning from Multisensory UAV Data., , , , и . Remote. Sens., 14 (19): 4786 (2022)Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping., , , и . Sensors, 17 (1): 214 (2017)Remote Sensing of Explosives-Induced Stress in Plants: Hyperspectral Imaging Analysis for Remote Detection of Unexploded Threats., , , и . Remote Sensing, 11 (15): 1827 (2019)Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM., , , , , , и . ECCV Workshops (6), том 12540 из Lecture Notes in Computer Science, стр. 433-449. Springer, (2020)Root Identification in Minirhizotron Imagery with Multiple Instance Learning., , , , , , и . CoRR, (2019)Overcoming Small Minirhizotron Datasets Using Transfer Learning., , , , , , , , и . CoRR, (2019)LabelStoma: A tool for stomata detection based on the YOLO algorithm., , , , , , , , , и 2 other автор(ы). Comput. Electron. Agric., (2020)UAV-Based High Resolution Thermal Imaging for Vegetation Monitoring, and Plant Phenotyping Using ICI 8640 P, FLIR Vue Pro R 640, and thermoMap Cameras., , , , , , , , , и 4 other автор(ы). Remote. Sens., 11 (3): 330 (2019)A New 4D-RGB Mapping Technique for Field-Based High-Throughput Phenotyping., , и . BMVC, стр. 322. BMVA Press, (2018)Crop Monitoring Using Satellite/UAV Data Fusion and Machine Learning., , , , , и . Remote. Sens., 12 (9): 1357 (2020)