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Parliament prowess, school science, and IChemE elections: News from the College
Welcome to the Intelligent Digital Systems Lab at Imperial College
The iDSL lab is part of the Electrical and Electronic Engineering Department of Imperial College London.
Welcome to the Intelligent Digital Systems Lab webpage.
2nd Workshop on Reconfigurable Computing for Machine Learning (RCML'2018) in FPL 2018 is co-organised by Dr.Bouganis.
"CascadeCNN: Pushing the performance limits of CNN quantisation" accepted on FPL'2018 (Preprint to be released soon).
We had a great time demonstrating our drone research in this year's Imperial Festival.
Stylianos presenting an overview of our work in Deployment of DNNs in the Embedded Space. (slides)
CascadeCNN: Our novel 2-stage CNN inference accelerator is presented on SysML 2018 inaugural conference. (Click to read the Extended Abstract )
Dr.Bouganis introduces 12-year students to our work on Convolutional Neural Networks.
"Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions" accepted on ACM Computing Surveys (Click to access the proposed CNN-to-FPGA Benchmark Suite).
fpgaConvNet is a framework developed in our lab to bridge the gap between DL developers and FPGAs
Dr.Bouganis is co-organising the 12th HiPEAC Workshop on Reconfigurable Computing (WRC'18)
Selected Publications: [Preprint] IROS 2018
Selected Publications: [Early Access] IEEE Transactions on Neural Networks and Learning Systems, 2018
Selected Publications: [Preprint] ACM Computing Surveys (2018)
Selected Publications: [Preprint] FPL 2018
Selected Publications: [Extended Abstract] SysML 2018
Selected Publications: [Preprint] ARC 2018
Selected Publications: FPL 2017
Selected Publications: FCCM 2016
Selected Publications: FCCM 2017
Selected Publications: LearningSys 2015
Selected Publications: IEEE Transactions on Circuits and Systems for Video Technology 2014
In the Intelligent Digital Systems Lab, we perform research towards high-performance (embedded) digital systems spanning several topic areas, including machine learning, computer vision, and robotics.