296 citations · 580 across the 22 of their papers we have counts for
37 papers
Inferring Facing Direction from Voice Signals
Yu-Lin Wei, Rui Li, Abhinav Mehrotra +2
Consider a home or office where multiple devices are running voice assistants (e.g., TVs, lights, ovens, refrigerators, etc.). A human user turns to a particular device and gives a…
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild
Mario Almeida, Stefanos Laskaridis, Abhinav Mehrotra +3
With smartphones' omnipresence in people's pockets, Machine Learning (ML) on mobile is gaining traction as devices become more powerful. With applications ranging from visual filte…
Temporal Kernel Consistency for Blind Video Super-Resolution
Lichuan Xiang, Royson Lee, Mohamed S. Abdelfattah +2
Deep learning-based blind super-resolution (SR) methods have recently achieved unprecedented performance in upscaling frames with unknown degradation. These models are able to accu…
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions
Royson Lee, Stylianos I. Venieris, Nicholas D. Lane
Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual apps spanning from on-demand movies and 360° videos to video-conferencing and live streami…
On-device Federated Learning with Flower
Akhil Mathur, Daniel J. Beutel, Pedro Porto Buarque de Gusmão +6
Federated Learning (FL) allows edge devices to collaboratively learn a shared prediction model while keeping their training data on the device, thereby decoupling the ability to do…
unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation
Stylianos I. Venieris, Javier Fernandez-Marques, Nicholas D. Lane
Single computation engines have become a popular design choice for FPGA-based convolutional neural networks (CNNs) enabling the deployment of diverse models without fabric reconfig…