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From R&D to Production – Optimising a Deep Learning Model for Deployment in an Embedded System Exemplified

Event: InCabin USA

| Session Date: Wednesday 22nd May

Hear from:

Peter Kristiansen cropped converted
Peter Kristiansen,
Head of Business Development,

The presentation aims to show that modern deep learning models, developed by academic purposes can, in a simple way, be adapted to run efficiently on embedded accelerators. This will be exemplified with performance measurements for a DL model designed for a Nvidia desktop GPU (RTX 3090) running on a Texas Instruments C7x DSP (TDA4) for a real time application with a minimal loss of accuracy.


The state-of-play in today's ADAS market

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