Solving Computer Vision Grand Challenges in One-Click
, Product Manager, NVIDIA
, Senior Software Engineer, NVIDIA
, Senior Data Science Engineer, NVIDIA
Highly Rated
From synthetic data generation and dataset augmentation to a growing suite of API-driven Metropolis microservices for multi-camera tracking & analytics, and more. As vision AI products become increasingly complex, models require robust diverse data, and deployments become more distributed, the need for better ways to facilitate the creation and deployment of apps becomes critical for developers. We’ll showcase how we’re supporting developers to turn their vision AI ideas into reality in weeks (rather than months), even for models with the most modest datasets.
In this session, we’ll demonstrate NVIDIA’s fundamental tools, such as using synthetic data generation with NVIDIA Isaac Sim, transfer learning with NVIDIA TAO, and pre-built microservices from NVIDIA Metropolis. Now, any developer can deploy sophisticated cloud-native vision AI applications that use modern computer vision capabilities such as multi-camera tracking, smart space analytics, or smart self-checkout.