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Syed Sha Qutub
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- affiliation: Technical University of Munich, Germany
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Conference and Workshop Papers
- 2023
- [c7]Syed Sha Qutub, Neslihan Köse Cihangir, Rafael Rosales, Michael Paulitsch, Korbinian Hagn, Florian Geissler, Yang Peng, Gereon Hinz, Alois C. Knoll:
BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture. BMVC 2023: 792-797 - [c6]Ralf Gräfe, Syed Sha Qutub, Florian Geissler, Michael Paulitsch:
Large-Scale Application of Fault Injection into PyTorch Models -an Extension to PyTorchFI for Validation Efficiency. DSN-S 2023: 56-62 - [c5]Florian Geissler, Syed Sha Qutub, Michael Paulitsch, Karthik Pattabiraman:
A Low-Cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks. SAFECOMP 2023: 75-88 - [c4]Ali Asgari Khoshouyeh
, Florian Geissler
, Syed Sha Qutub
, Michael Paulitsch
, Prashant J. Nair
, Karthik Pattabiraman
:
Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults. SC 2023: 85:1-85:17 - 2022
- [c3]Syed Sha Qutub
, Florian Geissler
, Yang Peng
, Ralf Gräfe, Michael Paulitsch
, Gereon Hinz, Alois C. Knoll:
Hardware Faults that Matter: Understanding and Estimating the Safety Impact of Hardware Faults on Object Detection DNNs. SAFECOMP 2022: 298-318 - 2021
- [c2]Florian Geissler, Syed Sha Qutub, Sayanta Roychowdhury, Ali Asgari Khoshouyeh, Yang Peng, Akash Dhamasia, Ralf Graefe, Karthik Pattabiraman, Michael Paulitsch:
Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision. AISafety@IJCAI 2021 - 2020
- [c1]Syed Sha Qutub
, Oliver Grau, Korbinian Hagn:
DNN Analysis through Synthetic Data Variation. CSCS 2020: 4:1-4:10
Informal and Other Publications
- 2024
- [i7]Syed Sha Qutub, Michael Paulitsch, Korbinian Hagn, Neslihan Köse Cihangir, Kay-Ulrich Scholl, Fabian Oboril, Gereon Hinz, Alois Knoll:
Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection. CoRR abs/2406.03188 (2024) - [i6]Syed Sha Qutub, Michael Paulitsch, Karthik Pattabiraman, Korbinian Hagn, Fabian Oboril, Cornelius Bürkle, Kay-Ulrich Scholl, Gereon Hinz, Alois Knoll:
Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models. CoRR abs/2406.03229 (2024) - 2023
- [i5]Syed Sha Qutub, Neslihan Kose, Rafael Rosales, Michael Paulitsch, Korbinian Hagn, Florian Geissler, Yang Peng, Gereon Hinz, Alois Knoll:
BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture. CoRR abs/2309.08036 (2023) - [i4]Ralf Gräfe, Syed Sha Qutub, Florian Geissler, Michael Paulitsch:
Large-Scale Application of Fault Injection into PyTorch Models - an Extension to PyTorchFI for Validation Efficiency. CoRR abs/2310.19449 (2023) - [i3]Florian Geissler, Syed Sha Qutub, Michael Paulitsch, Karthik Pattabiraman:
A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks. CoRR abs/2310.20349 (2023) - 2022
- [i2]Syed Sha Qutub, Florian Geissler, Yang Peng, Ralf Gräfe, Michael Paulitsch, Gereon Hinz, Alois C. Knoll:
Hardware faults that matter: Understanding and Estimating the safety impact of hardware faults on object detection DNNs. CoRR abs/2209.03225 (2022) - 2021
- [i1]Florian Geissler, Syed Sha Qutub, Sayanta Roychowdhury, Ali Asgari Khoshouyeh, Yang Peng, Akash Dhamasia, Ralf Graefe, Karthik Pattabiraman, Michael Paulitsch:
Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision. CoRR abs/2108.07019 (2021)
Coauthor Index
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