Tuesday 5th May, 2015
2:20pm to 3:00pm
This session will reveal a novel use of Convolutional Neural Networks (CNNs) as a Deep Learning architecture towards the creation of a facial expression recognition vocabulary. The first half of this session will cover how this new approach in the IoT space allows vision software algorithms to read micro-expressions in real-time with a high level of accuracy, speed and customization. The second half of this session will reveal a number of current industry verticals, in the IoT space and others, that are benefiting today from integrating emotion recognition technology into their commercial applications to amplify context awareness; and subsequently, enhance users experiences through better Ambient Intelligence. This session will include a highly rated live demo on stage!
Modar is a serial entrepreneur and expert in AI-based vision software development and Ambient Intelligence (AmI). He is currently founder and CEO at Eyeris, developer of a Deep Learning-based emotion recognition software, EmoVu, that reads facial micro-expressions. Eyeris uses Convolutional Neural Networks (CNN's) as a Deep Learning architecture to train and deploy its algorithm in to a number of today’s commercial applications. Modar combines a decade of experience between Human Machine Interaction (HMI) and Audience Behavioral Measurement. He is a frequent keynoter on “Ambient Intelligence”, a winner of several technology and innovation awards and has been featured in many major publications for his work.
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