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Nael Fasfous
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2020 – today
- 2024
- [c25]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 - [c24]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 - [c23]Shaown Mojumder, Simon Friedrich, Emil Matús, Gerhard P. Fettweis, Matthias Lüders, Martin Friedrich, Oliver Renke, Holger Blume, Julian Höfer, Patrick Schmidt, Jürgen Becker, Darius Grantz, Markus Kock, Jens Benndorf, Nael Fasfous, Pierpaolo Morì, Hans-Jörg Vögel, Samira Ahmadifarsani, Leonidas Kontopoulos, Ulf Schlichtmann, Kay Bierzynski:
ZuSE-KI-Mobil AI Chip Design Platform: An Overview. NorCAS 2024: 1-7 - [c22]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
- [c21]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 - [c20]Sebastian Karl, Arne Symons
, Nael Fasfous, Marian Verhelst
Genetic Algorithm-based Framework for Layer-Fused Scheduling of Multiple DNNs on Multi-core Systems. DATE 2023: 1-6 - [c19]Fabian Kempf, Julian Höfer
The ZuSE-KI-Mobil AI Accelerator SoC: Overview and a Functional Safety Perspective. DATE 2023: 1-6 - [c18]Simon Friedrich, Shambhavi Balamuthu Sampath, Robert Wittig, Manoj Rohit Vemparala, Nael Fasfous, Emil Matús, Walter Stechele, Gerhard P. Fettweis:
Lightweight Instruction Set for Flexible Dilated Convolutions and Mixed-Precision Operands. ISQED 2023: 1-8 - 2022
- [b1]Nael Fasfous:
Hardware-Software Co-Design of Deep Neural Networks: From Handcrafted to Automated Design and Deployment. Technical University of Munich, Germany, 2022 - [j4]Mark Sagi
Fine-Grained Power Modeling of Multicore Processors Using FFNNs. Int. J. Parallel Program. 50(2): 243-266 (2022) - [j3]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Emanuele Valpreda
HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology. Leibniz Trans. Embed. Syst. 8(1): 03:1-03:30 (2022) - [c17]Pierpaolo Morì, Manoj Rohit Vemparala, Nael Fasfous, Saptarshi Mitra
Accelerating and pruning CNNs for semantic segmentation on FPGA. DAC 2022: 145-150 - [c16]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda
AnaCoNGA: Analytical HW-CNN Co-Design Using Nested Genetic Algorithms. DATE 2022: 238-243 - [c15]Nael Fasfous, Lukas Frickenstein, Michael Neumeier, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda
Mind the Scaling Factors: Resilience Analysis of Quantized Adversarially Robust CNNs. DATE 2022: 706-711 - 2021
- [j2]Akshay Srivatsa
Exploring a Hybrid Voting-based Eviction Policy for Caches and Sparse Directories on Manycore Architectures. Microprocess. Microsystems 87: 104384 (2021) - [j1]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda
HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology. ACM Trans. Embed. Comput. Syst. 20(5s): 66:1-66:25 (2021) - [c14]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 - [c13]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Sreetama Sarkar, Qi Zhao
Adversarial Robust Model Compression Using In-Train Pruning. CVPR Workshops 2021: 66-75 - [c12]Mark Sagi, Martin Rapp, Heba Khdr, Yizhe Zhang, Nael Fasfous, Nguyen Anh Vu Doan, Thomas Wild, Jörg Henkel, Andreas Herkersdorf:
Long Short-Term Memory Neural Network-based Power Forecasting of Multi-Core Processors. DATE 2021: 1685-1690 - [c11]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Mohamed Badawy, Felix Hundhausen, Julian Höfer
Binary-LoRAX: Low-Latency Runtime Adaptable XNOR Classifier for Semi-Autonomous Grasping with Prosthetic Hands. ICRA 2021: 13430-13437 - [c10]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 - [c9]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 - [c8]Manoj Rohit Vemparala, Anmol Singh, Ahmed Mzid, Nael Fasfous, Alexander Frickenstein, Florian Mirus, Hans-Jörg Vögel, Naveen Shankar Nagaraja, Walter Stechele:
Pruning CNNs for LiDAR-based Perception in Resource Constrained Environments. IV Workshops 2021: 228-235 - [c7]Ee Heng Chen, Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Ahmed Mzid, Naveen Shankar Nagaraja, Jöran Zeisler, Walter Stechele:
Investigating Binary Neural Networks for Traffic Sign Detection and Recognition. IV 2021: 1400-1405 - [i4]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) - [i3]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) - [i2]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) - 2020
- [c6]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 - [c5]Alexander Frickenstein, Manoj Rohit Vemparala, Nael Fasfous, Laura Hauenschild, Naveen Shankar Nagaraja, Christian Unger, Walter Stechele:
ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks. DAC 2020: 1-6 - [c4]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Walter Stechele:
OrthrusPE: Runtime Reconfigurable Processing Elements for Binary Neural Networks. DATE 2020: 1662-1667 - [c3]Nguyen Anh Vu Doan, Akshay Srivatsa, Nael Fasfous, Sebastian Nagel, Thomas Wild, Andreas Herkersdorf:
On-Chip Democracy: A Study on the Use of Voting Systems for Computer Cache Memory Management. IEEM 2020: 984-988 - [c2]Akshay Srivatsa, Sebastian Nagel, Nael Fasfous, Nguyen Anh Vu Doan, Thomas Wild, Andreas Herkersdorf:
HyVE: A Hybrid Voting-based Eviction Policy for Caches. NorCAS 2020: 1-7 - [c1]Mark Sagi, Nguyen Anh Vu Doan, Nael Fasfous, Thomas Wild, Andreas Herkersdorf:
Fine-Grained Power Modeling of Multicore Processors Using FFNNs. SAMOS 2020: 186-199 - [i1]Alexander Frickenstein, Manoj Rohit Vemparala, Nael Fasfous, Laura Hauenschild, Naveen Shankar Nagaraja, Christian Unger, Walter Stechele:
ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks. CoRR abs/2007.13384 (2020)
Coauthor Index
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last updated on 2024-11-27 20:31 CET by the dblp team
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