296 citations · 458 across the 12 of their papers we have counts for
14 papers · 1 filter
Multi-Exit Semantic Segmentation Networks
Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis +1
Semantic segmentation arises as the backbone of many vision systems, spanning from self-driving cars and robot navigation to augmented reality and teleconferencing. Frequently oper…
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…
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…
HAPI: Hardware-Aware Progressive Inference
Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim +1
Convolutional neural networks (CNNs) have recently become the state-of-the-art in a diversity of AI tasks. Despite their popularity, CNN inference still comes at a high computation…
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs
Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris +1
Large-scale convolutional neural networks (CNNs) suffer from very long training times, spanning from hours to weeks, limiting the productivity and experimentation of deep learning…
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors
Royson Lee, Stylianos I. Venieris, Łukasz Dudziak +2
In recent years, convolutional networks have demonstrated unprecedented performance in the image restoration task of super-resolution (SR). SR entails the upscaling of a single low…