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Feature-based speed limit sign detection using a graphics processing unit., , , and . Intelligent Vehicles Symposium, page 195-200. IEEE, (2011)FPGA versus GPU for Speed-Limit-Sign Recognition., , , and . ITSC, page 843-850. IEEE, (2018)A Template-Based Approach for Real-Time Speed-Limit-Sign Recognition on an Embedded System Using GPU Computing., , , and . DAGM-Symposium, volume 6376 of Lecture Notes in Computer Science, page 162-171. Springer, (2010)Specialized Cyclist Detection Dataset: Challenging Real-World Computer Vision Dataset for Cyclist Detection Using a Monocular RGB Camera., , , , , , and . IV, page 114-118. IEEE, (2019)Utilizing Weak Supervision to Infer Complex Objects and Situations in Autonomous Driving Data., , , , and . IV, page 119-125. IEEE, (2019)Benchmarking Deep Learning Frameworks and Investigating FPGA Deployment for Traffic Sign Classification and Detection., , , , and . IEEE Trans. Intelligent Vehicles, 4 (3): 385-395 (2019)Efficient occupancy grid computation on the GPU with lidar and radar for road boundary detection., , , and . Intelligent Vehicles Symposium, page 1006-1013. IEEE, (2010)Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset., , , and . Intelligent Vehicles Symposium, page 1197-1203. IEEE, (2018)PointAtMe: Efficient 3D Point Cloud Labeling in Virtual Reality., , , and . IV, page 1693-1698. IEEE, (2019)