Autonomous vehicles of the future will require reliable perception-analysis-learning capabilities and computational horsepower of a supercomputer. PathPartner’s engineering services coupled with high-performance product accelerators are designed to help organizations quickly develop next wave of vision based ADAS and fully autonomous solutions.
Cascade of detection and classification neural networks to detect traffic signs and classifying them to 43 sign classes
Implementation of Traffic sign recognition, Object detection, Pedestrian detection and Road lane marking on Nvidia Jetson AGX Xavier
Robust face recognition that takes into account a host of influential factors such as varied illumination conditions, posses and expression
Deep neural network(DNN) based pedestrian detection to detect and localize pedestrians
Development of algorithms for generating depth map from stereo camera on KITTI stereo
Efficient implementation of CNN kernels exploiting SIMD and VLIW capability
