296 citations · 457 across the 10 of their papers we have counts for
21 papers
Multi-DNN Accelerators for Next-Generation AI Systems
Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane
As the use of AI-powered applications widens across multiple domains, so do increase the computational demands. Primary driver of AI technology are the deep neural networks (DNNs).…
OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices
Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris
Radical progress in the field of deep learning (DL) has led to unprecedented accuracy in diverse inference tasks. As such, deploying DL models across mobile platforms is vital to e…
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…
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…
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation
Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris +1
On-device machine learning is becoming a reality thanks to the availability of powerful hardware and model compression techniques. Typically, these models are pretrained on large G…
Neural Enhancement in Content Delivery Systems: The State-of-the-Art 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-degree videos to video-conferencing and live s…