Lukas Frickenstein

According to our database, Lukas Frickenstein authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Wino Vidi Vici: Conquering Numerical Instability of 8-bit Winograd Convolution for Accurate Inference Acceleration on Edge.

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

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

WinoTrain: Winograd-Aware Training for Accurate Full 8-bit Convolution Acceleration.

Pierpaolo Morì, Shambhavi Balamuthu Sampath, Lukas Frickenstein, Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Walter Stechele, Claudio Passerone

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

Mind the Scaling Factors: Resilience Analysis of Quantized Adversarially Robust CNNs.

Nael Fasfous, Lukas Frickenstein, Michael Neumeier, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda, Maurizio Martina, Walter Stechele

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Accelerating and pruning CNNs for semantic segmentation on FPGA.

Pierpaolo Morì, Manoj Rohit Vemparala, Nael Fasfous, Saptarshi Mitra, Sreetama Sarkar, Alexander Frickenstein, Lukas Frickenstein, Domenik Helms, Naveen Shankar Nagaraja, Walter Stechele, Claudio Passerone

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021

BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and Positioning Predictor on Edge Devices.

Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Lukas Frickenstein, Walter Stechele

CoRR, 2021

BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and Positioning Predictor on Edge Devices.

Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Lukas Frickenstein, Mohamed Badawy, Walter Stechele

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

BreakingBED: Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks.

Manoj Rohit Vemparala, Alexander Frickenstein, Nael Fasfous, Lukas Frickenstein, Qi Zhao, Sabine Kuhn, Daniel Ehrhardt, Yuankai Wu, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele

Proceedings of the Intelligent Systems and Applications, 2021

Adversarial Robust Model Compression Using In-Train Pruning.

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Hardware-Aware Mixed-Precision Neural Networks using In-Train Quantization.

Manoj Rohit Vemparala, Nael Fasfous, Lukas Frickenstein, Alexander Frickenstein, Anmol Singh, Driton Salihu, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

L2PF - Learning to Prune Faster.

Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Mhd Ali Moraly, Aquib Jamal, Lukas Frickenstein, Christian Unger, Naveen Shankar Nagaraja, Walter Stechele

Proceedings of the Computer Vision and Image Processing - 5th International Conference, 2020