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SimuGAN: Unsupervised Forward Modeling and Optimal Design of a LIDAR Camera
Project type
Research POC - generative AI
Date
August 2020 - December 2020
Location
Haifa, Israel
Customer
RealSense - Intel
SimuGAN is a project that focuses on the development of a GAN-based algorithm that learns to mimic the behavior of an energy-saving LIDAR camera for short distances. The algorithm first learns the LIDAR behavior for further optimization and camera parameter calibration.
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