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Exploiting LIDAR-based features on pedestrian detection in urban scenarios.

, , and . ITSC, page 1-6. IEEE, (2009)

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Look and Listen: A Multi-modality Late Fusion Approach to Scene Classification for Autonomous Machines., , , , and . IROS, page 10380-10385. IEEE, (2020)Improving Localization by Learning Pole-Like Landmarks Using a Semi-supervised Approach., , , , and . ROBOT (1), volume 1092 of Advances in Intelligent Systems and Computing, page 255-266. Springer, (2019)Reducing Overconfidence Predictions in Autonomous Driving Perception., , , , and . IEEE Access, (2022)Probabilistic Approach for Road-Users Detection., , , , , , and . IEEE Trans. Intell. Transp. Syst., 24 (9): 9253-9267 (September 2023)Pedestrian detection in far infrared images., , , , and . Integr. Comput. Aided Eng., 20 (4): 347-360 (2013)Reducing Overconfidence Predictions for Autonomous Driving Perception., , , , and . CoRR, (2022)An RRT-based navigation approach for mobile robots and automated vehicles., , , and . INDIN, page 326-331. IEEE, (2014)LSTM and GPT-2 Synthetic Speech Transfer Learning for Speaker Recognition to Overcome Data Scarcity., , , , and . CoRR, (2020)Multimodal vehicle detection: fusing 3D-LIDAR and color camera data., , , , and . Pattern Recognit. Lett., (2018)HMAPs - Hybrid Height- Voxel Maps for Environment Representation., , , and . IROS, page 1197-1203. IEEE, (2018)