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Using Deep Learning to Challenge Safety Standard for Highly Autonomous Machines in Agriculture., , , and . J. Imaging, 2 (1): 6 (2016)The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation., , , and . CVPR Workshops, page 2703-2710. Computer Vision Foundation / IEEE, (2019)Baggage Routing with Scheduled Departures using Deep Reinforcement Learning., , and . ISCSIC, page 13-19. IEEE, (2021)The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture., , , , , , , , and . CVPR Workshops, page 2676-2684. Computer Vision Foundation / IEEE, (2019)FieldSAFE: Dataset for Obstacle Detection in Agriculture., , , , , , , and . CoRR, (2017)Using Illumination Changes to Synchronize Eye Tracking in Visual Paradigms., and . BIOSTEC (Selected Papers), volume 511 of Communications in Computer and Information Science, page 289-298. Springer, (2014)Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation., , , , , and . Frontiers Robotics AI, (2018)Weed Classification Using Explainable Multi-Resolution Slot Attention., , , , and . Sensors, 21 (20): 6705 (2021)Sparse-to-Dense Depth Completion in Precision Farming., , , , and . ICVISP, page 35:1-35:5. ACM, (2019)Synchronization of Electroencephalography and Eye Tracking using Global Illumination Changes., , and . BIOSIGNALS, page 55-60. SciTePress, (2014)