Steven Kim, Co-CEO of Nota America, presents the “How to Select, Train, Optimize and Deploy Edge Vision AI Models in Three Days” tutorial at the May 2023 Embedded Vision Summit.
NetsPresso, as explained by Kim in this presentation, is a development pipeline that enables developers to build, optimize and deploy vision AI models faster and better. Using conventional tools, it typically takes 6-12 weeks to select, train, optimize and deploy a vision DNN. Using NetsPresso, developers can create and deploy high-performance models at the edge in three days.
NetsPresso uses neural architecture search to quickly find the best model for your application and hardware, and then trains the model in a hardware-aware manner to optimize accuracy and latency for your processor. Then NetsPresso applies model compression and acceleration to make your model small and fast without sacrificing accuracy. Finally, NetsPresso generates executable code and packages it in a form that can easily be integrated into your application. While developers focus on optimizing model accuracy and latency, NetsPresso minimizes the time and money required to build these models. So far, AI models developed through NetsPresso are commercially deployed on more than 45,000 devices.
See here for a PDF of the slides.