Speaker "JR Alaoui" Details Back



User behavioral predictive analytics through deep learning-based emotion recognition


This session will introduce embedding Deep learning-based vision software that reads facial micro-expressions in real-time into various camera-enabled devices that we use everyday.
Today’s Advanced Computer Vision Technologies rely primarily on image and pattern recognition through vision sensors; facial expression recognition; however, relies – for the most part – on the hybrid of both. A large number of applications can benefit the IoT, automotive and Consumer Electronics eco-system by adding Artificially Intelligent Emotion Recognition and Vision Sensing to the mix.
Using Deep Learning on Convolutional Neural Networks (CNNs) alongside Advanced Machine Learning Techniques, vision algorithms for embedded systems can now allow today’s and future camera-enabled devices and machines to become “Affective Devices” that recognize the full range of facial emotions – including Joy, Surprise, Anger, Fear, disgust, Sadness and neutral, along with Mood Indicators and other facial behavioral metrics, faster than real-time, in a 30th of a second. 
A large number of applications in a wide range of industries including gaming, healthcare, smart avatars, robotics, automotive and others can benefit from embedding the next generation Emotional Intelligence, for a full immersive Context Awareness Experience through Ambient Intelligence.
This session also includes a highly rated 1-minute Live Demo of the technology 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.