Lukas Frickenstein

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 13

Top Topics

Top Venues

Publications

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)
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)
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)
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)
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)
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)
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 (2021)
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 (2021)
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)
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)
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 (2021)
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)
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)