Syed Sha Qutub

dblp:280/1566 · DBLP profile ↗
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4ranked-venue papers
2as first author
4since 2021 · last 2023
0000-0002-7124-1835ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2 · 1 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2023 BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture
Syed Sha Qutub, Neslihan Kose, Rafael Rosales, Michael Paulitsch, Korbinian Hagn, Florian Geissler, Gereon Hinz, Alois C. Knoll
BMVC1
2023 A Low-Cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks
Florian Geissler, Syed Sha Qutub, Michael Paulitsch, Karthik Pattabiraman
SAFECOMP2
2023 Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults
abstract
The advent of High-Performance Computing has led to the adoption of Convolutional Neural Networks (CNNs) in safety-critical applications such as autonomous vehicles. However, CNNs are vulnerable to DRAM errors corrupting their parameters, thereby degrading their accuracy. Existing techniques for protecting CNNs from DRAM errors are either expensive or fail to protect from large-granularity, multi-bit errors, which occur commonly in DRAMs.
Ali Asgari Khoshouyeh, Florian Geissler, Syed Sha Qutub, Michael Paulitsch, Prashant J. Nair, Karthik Pattabiraman
SC3
2022 Hardware Faults that Matter: Understanding and Estimating the Safety Impact of Hardware Faults on Object Detection DNNs
Syed Sha Qutub, Florian Geissler, Ralf Gräfe, Michael Paulitsch, Gereon Hinz, Alois C. Knoll
SAFECOMP1