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Experimental validation of lane-change intention prediction methodologies based on CNN and LSTM.

, , , , and . ITSC, page 3657-3662. IEEE, (2019)

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An Experimental Study on Pitch Compensation in Pedestrian-Protection Systems for Collision Avoidance and Mitigation., , , , , and . IEEE Trans. Intell. Transp. Syst., 10 (3): 469-474 (2009)Robust visual odometry for vehicle localization in urban environments., , , and . Robotica, 28 (3): 441-452 (2010)Automatic LightBeam Controller for driver assistance., , , , , , and . Mach. Vis. Appl., 22 (5): 819-835 (2011)The PREVENTION Challenge: How Good Are Humans Predicting Lane Changes?, , , , and . IV, page 45-50. IEEE, (2020)Automatic Traffic Signs and Panels Inspection System Using Computer Vision., , , , , , , , , and 1 other author(s). IEEE Trans. Intell. Transp. Syst., 12 (2): 485-499 (2011)SVM-based Obstacles Recognition for Road Vehicle Applications., , , , , , and . IJCAI, page 1740-1741. Professional Book Center, (2005)Experimental validation of lane-change intention prediction methodologies based on CNN and LSTM., , , , and . ITSC, page 3657-3662. IEEE, (2019)Assessment of distractions inferred by in-vehicle information systems on a naturalistic simulator., , , , , , , and . ITSC, page 1279-1284. IEEE, (2011)Pedestrian path prediction based on body language and action classification., , , and . ITSC, page 679-684. IEEE, (2014)Real-Time Vision-Based Vehicle Detection for Rear-End Collision Mitigation Systems., , , , , , and . EUROCAST, volume 5717 of Lecture Notes in Computer Science, page 320-325. Springer, (2009)