Building Efficient CNN Models for Mobile and Embedded Applications

Wednesday, May 23, 2:10 PM - 2:40 PM
Summit Track: 
Technical Insights I
Mission City Ballroom B2-B5

Recent advances in efficient deep learning models have led to many potential applications in mobile and embedded devices. In this talk, I will discuss state-of-the-art model architectures, and introduce our work on real-time style transfer and pose estimation on mobile phones.


Peter Vajda

Research Scientist, Facebook

Peter Vajda is a Research Scientist working on computer vision at Facebook since 2014. Before joining Facebook, he was a Visiting Assistant Professor in Professor Bernd Girod’s group in Stanford University, Stanford, USA. He was working on personalized multimedia system and mobile visual search. Peter received a M.Sc. in Computer Science from the Vrije Universiteit, Amsterdam, Netherlands and a M.Sc. in Program Designer Mathematician from Eötvös Loránd University, Budapest, Hungary. Peter completed his Ph.D. with Prof. Touradj Ebrahimi at the Ecole Polytechnique Fédéral de Lausanne (EPFL), Lausanne, Switzerland, 2012.

See you at the Summit! May 20-23 in Santa Clara, California!
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