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Conference and Workshop Papers
- 2024
[c11]Lukas Frickenstein, Pierpaolo Morì, Shambhavi Balamuthu Sampath, Moritz Thoma, Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Christian Unger, Claudio Passerone, Walter Stechele:
Pruning as a Binarization Technique. CVPR Workshops 2024: 2131-2140- [c10]Pierpaolo Morì, Moritz Thoma, Lukas Frickenstein, Shambhavi Balamuthu Sampath, Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Walter Stechele, Daniel Mueller-Gritschneder, Claudio Passerone:
MATAR: Multi-Quantization-Aware Training for Accurate and Fast Hardware Retargeting. DATE 2024: 1-6 - [c9]Pierpaolo Morì, Lukas Frickenstein, Shambhavi Balamuthu Sampath, Moritz Thoma, Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Christian Unger, Walter Stechele, Daniel Mueller-Gritschneder, Claudio Passerone:
Wino Vidi Vici: Conquering Numerical Instability of 8-bit Winograd Convolution for Accurate Inference Acceleration on Edge. WACV 2024: 53-62 - 2023
- [c8]Pierpaolo Morì, Shambhavi Balamuthu Sampath, Lukas Frickenstein, Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Walter Stechele, Claudio Passerone:
WinoTrain: Winograd-Aware Training for Accurate Full 8-bit Convolution Acceleration. DAC 2023: 1-6 - 2022
- [c7]Pierpaolo Morì, Manoj Rohit Vemparala, Nael Fasfous, Saptarshi Mitra
, Sreetama Sarkar, Alexander Frickenstein, Lukas Frickenstein, Domenik Helms, Naveen Shankar Nagaraja, Walter Stechele, Claudio Passerone:
Accelerating and pruning CNNs for semantic segmentation on FPGA. DAC 2022: 145-150 - [c6]Nael Fasfous, Lukas Frickenstein, Michael Neumeier, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda, Maurizio Martina, Walter Stechele:
Mind the Scaling Factors: Resilience Analysis of Quantized Adversarially Robust CNNs. DATE 2022: 706-711 - 2021
- [c5]Manoj Rohit Vemparala, Nael Fasfous, Lukas Frickenstein, Alexander Frickenstein, Anmol Singh, Driton Salihu, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele:
Hardware-Aware Mixed-Precision Neural Networks using In-Train Quantization. BMVC 2021: 60 - [c4]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Sreetama Sarkar, Qi Zhao, Sabine Kuhn, Lukas Frickenstein, Anmol Singh, Christian Unger, Naveen Shankar Nagaraja, Christian Wressnegger, Walter Stechele:
Adversarial Robust Model Compression Using In-Train Pruning. CVPR Workshops 2021: 66-75 - [c3]Manoj Rohit Vemparala, Alexander Frickenstein, Nael Fasfous, Lukas Frickenstein, Qi Zhao, Sabine Kuhn, Daniel Ehrhardt, Yuankai Wu, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele:
BreakingBED: Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks. IntelliSys (1) 2021: 148-167 - [c2]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Lukas Frickenstein, Mohamed Badawy, Walter Stechele:
BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and Positioning Predictor on Edge Devices. IPDPS Workshops 2021: 108-115 - 2020
- [c1]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Mhd Ali Moraly, Aquib Jamal, Lukas Frickenstein, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele:
L2PF - Learning to Prune Faster. CVIP (3) 2020: 249-261
Informal and Other Publications
- 2021
- [i3]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Mhd Ali Moraly, Aquib Jamal, Lukas Frickenstein, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele:
L2PF - Learning to Prune Faster. CoRR abs/2101.02663 (2021) - [i2]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Lukas Frickenstein, Walter Stechele:
BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and Positioning Predictor on Edge Devices. CoRR abs/2102.03456 (2021) - [i1]Manoj Rohit Vemparala, Alexander Frickenstein, Nael Fasfous, Lukas Frickenstein, Qi Zhao, Sabine Kuhn, Daniel Ehrhardt, Yuankai Wu, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele:
BreakingBED - Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks. CoRR abs/2103.08031 (2021)
Coauthor Index
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