An Efficient FPGA Accelerator Design for Optimized CNNs Using OpenCL. - Manoj Rohit Vemparala; Alexander Frickenstein; Walter Stechele (ARCS, 2019)

Resource-Aware Optimization of DNNs for Embedded Applications. - Alexander Frickenstein; Christian Unger; Walter Stechele (CRV, 2019)

DSC: Dense-Sparse Convolution for Vectorized Inference of Convolutional Neural Networks. - Alexander Frickenstein; Manoj Rohit Vemparala; Christian Unger; Fatih Ayar; Walter Stechele (CVPR Workshops, 2019)

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 (CVIP (3), 2020)

ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks. - Alexander Frickenstein; Manoj Rohit Vemparala; Nael Fasfous; Laura Hauenschild; Naveen Shankar Nagaraja; Christian Unger; Walter Stechele (DAC, 2020)

OrthrusPE: Runtime Reconfigurable Processing Elements for Binary Neural Networks. - Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Walter Stechele (DATE, 2020)

Binary DAD-Net: Binarized Driveable Area Detection Network for Autonomous Driving. - Alexander Frickenstein; Manoj Rohit Vemparala; Jakob Mayr; Naveen Shankar Nagaraja; Christian Unger; Federico Tombari; Walter Stechele (ICRA, 2020)

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 (BMVC, 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 (CVPR Workshops, 2021)

Binary-LoRAX: Low-Latency Runtime Adaptable XNOR Classifier for Semi-Autonomous Grasping with Prosthetic Hands. - Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Mohamed Badawy; Felix Hundhausen; Julian Höfer; Naveen Shankar Nagaraja; Christian Unger; Hans-Jörg Vögel; Jürgen Becker 001; Tamim Asfour; Walter Stechele (ICRA, 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 (IntelliSys (1), 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 (IPDPS Workshops, 2021)

Investigating Binary Neural Networks for Traffic Sign Detection and Recognition. - Ee Heng Chen; Manoj Rohit Vemparala; Nael Fasfous; Alexander Frickenstein; Ahmed Mzid; Naveen Shankar Nagaraja; Jöran Zeisler; Walter Stechele (IV, 2021)

Pruning CNNs for LiDAR-based Perception in Resource Constrained Environments. - Manoj Rohit Vemparala; Anmol Singh; Ahmed Mzid; Nael Fasfous; Alexander Frickenstein; Florian Mirus; Hans-Jörg Vögel; Naveen Shankar Nagaraja; Walter Stechele (IV Workshops, 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)

HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology. - Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Emanuele Valpreda; Driton Salihu; Nguyen Anh Vu Doan; Christian Unger; Naveen Shankar Nagaraja; Maurizio Martina; Walter Stechele (ACM Trans. Embed. Comput. Syst., 2021)

HAPPi-Net: Hardware-Aware Performant Perception of Neural Networks. - Alexander Frickenstein (Shaker, 2021)

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 (DAC, 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 (DATE, 2022)

AnaCoNGA: Analytical HW-CNN Co-Design Using Nested Genetic Algorithms. - Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Emanuele Valpreda; Driton Salihu; Julian Höfer; Anmol Singh; Naveen Shankar Nagaraja; Hans-Jörg Vögel; Nguyen Anh Vu Doan; Maurizio Martina; Jürgen Becker 001; et al. (DATE, 2022)

HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology. - Manoj Rohit Vemparala; Nael Fasfous; Alexander Frickenstein; Emanuele Valpreda; Manfredi Camalleri; Qi Zhao; Christian Unger; Naveen Shankar Nagaraja; Maurizio Martina; Walter Stechele (Leibniz Trans. Embed. Syst., 2022)

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 (DAC, 2023)

The ZuSE-KI-Mobil AI Accelerator SoC: Overview and a Functional Safety Perspective. - Fabian Kempf; Julian Höfer; Tanja Harbaum; Jürgen Becker 001; Nael Fasfous; Alexander Frickenstein; Hans-Jörg Vögel; Simon Friedrich; Robert Wittig; Emil Matús; Gerhard P. Fettweis; Matthias Lüders; et al. (DATE, 2023)

Adversarial Robustness of Multi-bit Convolutional Neural Networks. - Lukas Frickenstein; Shambhavi Balamuthu Sampath; Pierpaolo Morì; Manoj Rohit Vemparala; Nael Fasfous; Alexander Frickenstein; Christian Unger; Claudio Passerone; Walter Stechele (IntelliSys (3), 2023)

Pruning as a Binarization Technique. - Lukas Frickenstein; Pierpaolo Morì; Shambhavi Balamuthu Sampath; Moritz Thoma; Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Christian Unger; Claudio Passerone; Walter Stechele (CVPR Workshops, 2024)

MATAR: Multi-Quantization-Aware Training for Accurate and Fast Hardware Retargeting. - Pierpaolo Morì; Moritz Thoma; Lukas Frickenstein; Shambhavi Balamuthu Sampath; Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Walter Stechele; Daniel Mueller-Gritschneder; Claudio Passerone (DATE, 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 (WACV, 2024)

RepFC: Universal Structural Reparametrization Block for High Performance, Lightweight Deep Neural Networks. - Shambhavi Balamuthu Sampath; Judeson Anthony Fernando; Moritz Thoma; Nael Fasfous; Lukas Frickenstein; Pierpaolo Morì; Manoj Rohit Vemparala; Alexander Frickenstein; Ulf Schlichtmann; Walter Stechele (CVPR Workshops, 2025)

Uncertainty Aware Training to Improve Uncertainty Active Learning for Semantic Segmentation. - Moritz Thoma; Tobias Preintner; Emad Aghajanzadeh; Shambhavi Balamuthu Sampath; Pierpaolo Morì; Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Daniel Mueller-Gritschneder; Ulf Schlichtmann (CVPR Workshops, 2025)

FLAR-SVD: Fast and Latency-Aware Singular Value Decomposition for Model Compression. - Moritz Thoma; Jorge Villasante; Emad Aghajanzadeh; Shambhavi Balamuthu Sampath; Pierpaolo Morì; Maximilian Groetzinger; Daniil Dylkin; Manoj Rohit Vemparala; Nael Fasfous; Alexander Frickenstein; Daniel Mueller-Gritschneder; Ulf Schlichtmann (CVPR Workshops, 2025)

HiFi-SAGE: High Fidelity GraphSAGE-Based Latency Estimators for DNN Optimization. - Shambhavi Balamuthu Sampath; Leon Hecht; Moritz Thoma; Lukas Frickenstein; Pierpaolo Morì; Nael Fasfous; Manoj Rohit Vemparala; Alexander Frickenstein; Walter Stechele; Daniel Mueller-Gritschneder; Claudio Passerone (DATE, 2025)