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ORCIDManoj Rohit Vemparala
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2020 – today
- 2024
[c22]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- [c21]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 - [c20]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
- [b1]Manoj Rohit Vemparala:
Hardware Aware Robust Compression of Neural Networks. Technical University of Munich, Germany, 2023 - [c19]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 - [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
- [j2]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Emanuele Valpreda
, Manfredi Camalleri, Qi Zhao, Christian Unger, Naveen Shankar Nagaraja, Maurizio Martina, Walter Stechele:
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, 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 - [c16]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, Walter Stechele:
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, Maurizio Martina, Walter Stechele:
Mind the Scaling Factors: Resilience Analysis of Quantized Adversarially Robust CNNs. DATE 2022: 706-711 - [c14]Adrian Osterwind, Julian Droste-Rehling, Manoj Rohit Vemparala, Domenik Helms:
Hardware Execution Time Prediction for Neural Network Layers. PKDD/ECML Workshops (1) 2022: 582-593 - 2021
- [j1]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda, Driton Salihu, Nguyen Anh Vu Doan, Christian Unger, Naveen Shankar Nagaraja, Maurizio Martina, Walter Stechele:
HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology. ACM Trans. Embed. Comput. Syst. 20(5s): 66:1-66:25 (2021) - [c13]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 - [c12]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 - [c11]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Mohamed Badawy, Felix Hundhausen, Julian Höfer, Naveen Shankar Nagaraja, Christian Unger, Hans-Jörg Vögel, Jürgen Becker, Tamim Asfour, Walter Stechele:
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 - [i5]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) - [i4]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) - [i3]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]Alexander Frickenstein, Manoj Rohit Vemparala, Jakob Mayr, Naveen Shankar Nagaraja, Christian Unger, Federico Tombari, Walter Stechele:
Binary DAD-Net: Binarized Driveable Area Detection Network for Autonomous Driving. ICRA 2020: 2295-2301 - [i2]Alexander Frickenstein, Manoj Rohit Vemparala, Jakob Mayr, Naveen Shankar Nagaraja, Christian Unger, Federico Tombari, Walter Stechele:
Binary DAD-Net: Binarized Driveable Area Detection Network for Autonomous Driving. CoRR abs/2006.08178 (2020) - [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)
2010 – 2019
- 2019
- [c2]Manoj Rohit Vemparala, Alexander Frickenstein, Walter Stechele:
An Efficient FPGA Accelerator Design for Optimized CNNs Using OpenCL. ARCS 2019: 236-249 - [c1]Alexander Frickenstein, Manoj Rohit Vemparala, Christian Unger, Fatih Ayar, Walter Stechele:
DSC: Dense-Sparse Convolution for Vectorized Inference of Convolutional Neural Networks. CVPR Workshops 2019: 1353-1360
Coauthor Index
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