Ekaterina Sirazitdinova, Data Scientist at NVIDIA, presents the “Fundamentals of Training AI Models for Computer Vision and Video Analytics Applications” tutorial at the May 2022 Embedded Vision Summit.

AI has become an important component of computer vision and video analytics applications. But creating AI-based solutions is a challenging process. To build a successful product, it is essential that training a deep neural network results in a model which is highly accurate, is robust to false positives and has high throughput.

While approaching a new computer vision and video analytics task, an AI engineer needs to make a number of design decisions. How do we formulate a deep learning problem? How much data is enough? How complex shall the model be for a particular task? How to set training parameters? In this two-part talk, Sirazitdinova shares some best practices an AI developer can follow to answer these and other important questions when developing a new AI system in order to get meaningful results faster.

See here for a PDF of the slides.

Part 1 Video

Part 2 Video

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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