Endava Synthetics presents its workflow for producing synthetic training data with an end-to-end pipeline built on top of Houdini. By leveraging Houdini’s core functionality and incorporating machine learning concepts, they produce synthetic datasets used to train machine vision algorithms to detect fillings and cavities in dental x-ray imagery – involving different x-ray types like bite wing and periapical, generating dental anatomy and defects, using synthetic data to aid routine analysis, freeing up dentist time for more complex tasks.
Jon Hanzelka is a Technical Art Director at Endava where he oversees the synthetic pipeline development and client engagement that enables machine learning solutions across a broad range of industry verticals. He has worked in tech and entertainment for over 18 years; contributing to films such as The Avengers, Inception, and The Dark Knight Rises and helping ship products like Microsoft HoloLens v1 and 2. For the past 8 years he has been…