08 Oct, 2019 (Tue)Time:
SpeakerProf. Wayne Luk,
Faculty of Engineering,
Department of Computing,
Imperial College London
PLEASE NOTE THAT THE SEMINAR HAS BEEN CANCELLED!
This talk presents a 3D Convolutional Neural Network (CNN) for human action recognition. It introduces an efficient building unit called 3D-1 bottleneck residual block (3D-1 BRB) at the algorithm level, and a corresponding FPGA-based hardware architecture called F-E3D at hardware level. Based on 3D-1 BRB, a novel 3D CNN model called E3DNet is developed, which achieves nearly 37 times reduction in model size and 5% improvement in accuracy compared to standard 3D CNNs on the UCF101 dataset. Together with various hardware optimizations, the proposed F-E3D is nearly 13 times faster than a previous FPGA design for 3D CNNs, with performance and accuracy comparable to other state-of-the-art 3D CNN models on GPU platforms while requiring only 7% of their energy consumption.
Biography of the speaker:
Wayne Luk is Professor of Computer Engineering in Department of Computing at Imperial College London. He was Visiting Professor at Stanford University from 2006 to 2009. He founded and leads the Computer Systems Section at Imperial College. His research interests include reconfigurable computing, field-programmable technology, and design automation. He is a fellow of the IEEE and a fellow of the BCS.
All are welcome.
OrganizerDr. H.K.H. So
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