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Based on the foundation of proprietary technologies and a core “brain” built on a deep learning platform, SenseTime has rapidly opened up AI application in multiple vertical scenarios.
The system accurately and promptly recognizes pedestrians, motor vehicles, and non-motor vehicles in various complex road environments.
The system provides accurate analysis of the attributes and characteristics of vehicles in the scene, including motion status, direction, trajectory, and light signals of the vehicles.
The system accurately recognizes attributes and characteristics of pedestrians in the scene, including movements and body orientations of the pedestrians.
The system recognizes attributes of different roads and lanes under different environmental conditions in an accurate and fast manner.
The system supports accurate and fast perception of the scenes for pixel-level semiotic symbols so as to achieve scene modelling.
The system supports accurate and fast recognition of traffic signs and lights in complex road environments and understanding their meanings.
The system leverages mainly visual information and integrates multiple low-cost sensor solutions to achieve highly accurate real-time positioning in large-scale urban scenes.
The system achieves 3D geometric reconstruction and texture mapping for large-scale urban scenes with assistance of multi-perspective cameras, radars, satellite positioning, and inertial navigation systems to provide high-quality 3D map data for autonomous driving.
The system leverages accurate sensor results to make rational and logical decisions in driving route planning and vehicle control.
Fast deployment of neural networks on FPGA platform with efficient model compression and acceleration technology to achieve highly flexible, low-cost autonomous driving technology.