Friday

Room 1

14:45 - 15:45 (UTC+10)

Talk (60 min)

Beyond Sentiment Analysis: Real-time object detection with ML.NET

According to various researches, AI can improve manufacturing defect detection rates by up to 90% with the help of computer vision. Not only this, it also helped save $2 billion of counterfeit bills, just in the US. This clearly depicts that Computer Vision is very essential and productive for many industry verticals. Despite its importance for businesses, it requires a handful of resources to detect or classify an object from the given media or image.  But would you like to learn how can you overcome this problem and implement object detection in your solutions? Easy peasy! ML.NET solves this problem for you and we're going to see how you can now detect images that too in an absolute real time using the latest ML.NET Model Builder without having to worry about your slower machine and I will brief you why's that! In addition to this, we'll also learn about the tools it take to label your images as well as some other cool examples and some use-cases of ML.NET. All in all, it's going to be fun for folks who want to remain in the .NET world and solve complex computer vision problems.

.NET
Machine Learning

Arafat Tehsin

Arafat is a Solution Architect at EY and Microsoft MVP (AI). He has been working with Global ISVs of Microsoft and developing some next-gen solutions using cutting-edge Microsoft technologies.

Arafat co-founded Global AI - The Podcast which talks about everything around Microsoft AI. He's also an active contributor for the community and co-founded the Bot Builder Community Project on GitHub. He loves to code / write / speak about Microsoft Azure AI, .NET and Power Platform.