New European Project: dAIEDGE kicks-off in Kaiserslautern
Posted on September 11, 2023
Very excited and proud that gicLAB is part of the new European Network of Excellence “dAIEDGE” for distributed, trustworthy, efficient and scalable AI at the Edge!
We will be leading aspects of the software component related to compilers and integration with novel hardware.
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Paper accepted at IJCNN 2023
Posted on April 27, 2023
Our paper “Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks” has been accepted at International Joint Conference on Neural Networks (IJCNN) 2023. This work is a collaboration with our colleagues at STMicroelectronics and the first publication of our PETRAS project MAISE (Multimodal AI based Security at the Edge)....
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gicLAB presents Transfer-Tuning in AccML@HiPEAC
Posted on January 21, 2023
Our student Perry Gibson gave a short invited talk on Transfer-Tuning
at the Accelerated Machine Learning (AccML) workshop, in HiPEAC 2023, Tolousse, France.
Paper published in NeurIPS ML Safety Workshop
Posted on December 10, 2022
Nick Louloudakis (based at the University of Edinburgh) published a paper at the NeurIPS ML Safety Workshop 2022, called “Assessing Robustness of Image Recognition Models to Changes in the Computational Environment”.
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SECDA-TFLite Published in JPDC
Posted on November 11, 2022
Our paper “SECDA-TFLite: A Toolkit for Efficient Development of FPGA-based DNN Accelerators for Edge Inference”
has been accepted at Elsevier Journal of Parallel and Distributed Computing (JPDC).
In addition, our code is available as an open-source toolkit for the community.
Transfer-Tuning Published at PACT 2022
Posted on October 12, 2022
Our paper Transfer-Tuning was published at PACT 2022, along with an artifact review.
The preprint is available on arXiv.
See paper details in our publication list.
Bifrost Published at IEEE ISPASS 2022
Congratulations to first author Axel Stjerngren
Posted on May 22, 2022
See paper details in our publication list.
gicLAB receives funding for BonsAPPs AIMDDE project
Posted on January 25, 2022
gicLAB is undertaking a 2 month project for an AI in industry challenge
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SECDA Published at IEEE SBAC-PAD 2021
Congratulations to first author Jude Haris
Posted on October 28, 2021
Publication: SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference @ SBAC-PAD 2021. [IEEE paper] [arXiv] [Blogpost]