In this session, participants will dive into the realm of facial detection, analysis, and recognition using Azure Computer Vision services. As a fundamental aspect of artificial intelligence, the ability to detect human faces, analyze facial features and emotions, and identify individuals is crucial for numerous applications. Throughout the session, attendees will explore various options for face detection, analysis, and identification, gaining insights into considerations for effective face analysis. Additionally, participants will learn to leverage Azure's Computer Vision and Face services to detect faces, understand their capabilities, compare and match detected faces, and implement facial recognition techniques.

How do you think that a Start-up will benefit from this session?
Start-ups can harness the knowledge gained from this session to enhance their products and solutions by integrating advanced facial detection and recognition capabilities. By understanding the options and considerations for face analysis and implementing facial recognition using Azure Computer Vision services, start-ups can create innovative applications with improved user experiences and heightened security measures. This session equips start-ups with the essential skills and insights necessary to leverage AI capabilities effectively, positioning them for success in today's competitive landscape.

This session will focus on exploring various options for face detection, analyzing facial features and emotions, understanding the capabilities of Azure's Computer Vision and Face services, comparing and matching detected faces, and implementing facial recognition techniques.

Read More: https://aka.ms/Detect/analyze/recognize-faces

What will the attendees or a Start-up learn from the session?
Attendees, including AI Engineers and Developers, will gain proficiency in: Identifying options for face detection, analysis, and identification. Understanding considerations for effective face analysis. Detecting faces using Azure's Computer Vision service. Utilizing the capabilities of Azure's Face service. Comparing and matching detected faces. Implementing facial recognition techniques.

Speaker BIO- Viswanatha Swamy
He is an aspirant Software Architect and currently, he works at Applied Information Sciences. He is passionate about C#, ASP.NET, Azure, Performance testing/tuning, .NET Core, and Docker. He loves to learn about new technologies.

Social Handle- https://twitter.com/vishipayyallore