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Research of pedestrian detection for intelligent vehicle based on machine vision., , , , и . ROBIO, стр. 1172-1177. IEEE, (2009)Research on Fault Location of Process-Level Communication Networks in Smart Substation Based on Deep Neural Networks., , , , , , и . IEEE Access, (2020)Pedestrian detection for intelligent transportation systems combining AdaBoost algorithm and support vector machine., , , , и . Expert Syst. Appl., 39 (4): 4274-4286 (2012)The intelligent obstacle sensing and recognizing method based on D-S evidence theory for UGV., , , , и . Future Gener. Comput. Syst., (2019)A New Waters Hole Detection and Tracking Method for UGV in Cross-Country Environment., , , , и . Int. J. Pattern Recognit. Artif. Intell., 30 (8): 1655024:1-1655024:26 (2016)Pillar-based multilayer pseudo-image 3D object detection., , , , и . J. Electronic Imaging, (2024)Residual MBConv Submanifold Module for 3D LiDAR-based Object Detection., , и . IV, стр. 1720-1724. IEEE, (2022)Dense 3D Semantic SLAM of traffic environment based on stereo vision., , , , , и . Intelligent Vehicles Symposium, стр. 965-970. IEEE, (2018)Longitudinal Control Strategy of Collision Avoidance Warning System for Intelligent Vehicle Considering Drivers and Environmental Factors., , , , и . Intelligent Vehicles Symposium, стр. 31-36. IEEE, (2018)iPLUG: Personalized List Recommendation in Twitter., , , , , и . WISE (2), том 8181 из Lecture Notes in Computer Science, стр. 88-103. Springer, (2013)