Manoj Rohit Vemparala

According to our database, Manoj Rohit Vemparala authored at least 24 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• 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

Hardware Aware Robust Compression of Neural Networks.

Manoj Rohit Vemparala

PhD thesis, 2023

Lightweight Instruction Set for Flexible Dilated Convolutions and Mixed-Precision Operands.

Simon Friedrich, Shambhavi Balamuthu Sampath, Robert Wittig, Manoj Rohit Vemparala, Nael Fasfous, Emil Matús, Walter Stechele, Gerhard P. Fettweis

Proceedings of the 24th International Symposium on Quality Electronic Design, 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

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

Hardware Execution Time Prediction for Neural Network Layers.

Adrian Osterwind, Julian Droste-Rehling, Manoj Rohit Vemparala, Domenik Helms

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 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, Walter Stechele

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

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

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

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

Proceedings of the IEEE Intelligent Vehicles Symposium 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

Proceedings of the IEEE Intelligent Vehicles Symposium, 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

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, Tamim Asfour, Walter Stechele

Proceedings of the IEEE International Conference on Robotics and Automation, 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

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

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

OrthrusPE: Runtime Reconfigurable Processing Elements for Binary Neural Networks.

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

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 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

Proceedings of the 57th ACM/IEEE Design Automation Conference, 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

2019

DSC: Dense-Sparse Convolution for Vectorized Inference of Convolutional Neural Networks.

Alexander Frickenstein, Manoj Rohit Vemparala, Christian Unger, Fatih Ayar, Walter Stechele

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

An Efficient FPGA Accelerator Design for Optimized CNNs Using OpenCL.

Manoj Rohit Vemparala, Alexander Frickenstein, Walter Stechele

Proceedings of the Architecture of Computing Systems - ARCS 2019, 2019