About This Training
Automotive engineers are facing several hurdles to port their deep learning (DL) algorithms
to an embedded hardware target while delivering the optimum performance for their
applications and adhering to the production boundary conditions applicable to their system.
DL applications are quickly growing across the globe in use throughout the vehicle. In fact,
the DL segment for artificial intelligence (AI) in the automotive market is expected to grow
by over 45% CAGR from 2020 to 2026.
Explore ways of dealing with these challenges and view an example of an optimized workflow
for deploying deep learning in automotive production vehicles using the NXP eIQ
auto deep learning toolkit.