This session explores how DiUS built custom computer vision models deployed at the edge to enable Swoop Aero to safely and reliably cover vast distances and inhospitable terrain to solve some of society’s greatest challenges—for example, delivering a vaccine to a child in Africa or getting a camera above a flood zone in regional Australia. It also deep dives into some of the challenges faced by Swoop Aero when operating drones in remote locations with little or no internet connectivity and discusses how DiUS leveraged AWS machine learning services to accelerate the build of custom computer vision models, including data labeling, data preparation, model training, and deployment pipelines, as well as model optimisation and conversion for edge inference.
Speaker: Speaker: Shahin Namin, Machine Learning Specialist, DiUS. To stay connected, Join DiUS for a complimentary, two hour ML workshop to help you get started or navigate any challenges with your existing ML solutions
