no code implementations • 16 Apr 2024 • Adarsha Balaji, Ramyad Hadidi, Gregory Kollmer, Mohammed E. Fouda, Prasanna Balaprakash
Our NAS and HPS of (1) BraggNN achieves a 31. 03\% improvement in bragg peak detection accuracy with a 87. 57\% reduction in model size, and (2) PtychoNN achieves a 16. 77\% improvement in model accuracy and a 12. 82\% reduction in model size when compared to the baseline PtychoNN model.
no code implementations • 20 Sep 2023 • Mohamad Fakih, Rouwaida Kanj, Fadi Kurdahi, Mohammed E. Fouda
Automatic Speech Recognition systems have been shown to be vulnerable to adversarial attacks that manipulate the command executed on the device.
no code implementations • 30 May 2023 • Ayan Shymyrbay, Mohammed E. Fouda, Ahmed Eltawil
Deep neural networks have been proven to be highly effective tools in various domains, yet their computational and memory costs restrict them from being widely deployed on portable devices.
no code implementations • 28 Dec 2022 • Kamilya Smagulova, Mohammed E. Fouda, Ahmed Eltawil
The higher speed, scalability and parallelism offered by ReRAM crossbar arrays foster development of ReRAM-based next generation AI accelerators.
no code implementations • 11 Aug 2022 • Mariam Rakka, Mohammed E. Fouda, Pramod Khargonekar, Fadi Kurdahi
Mixed-precision Deep Neural Networks achieve the energy efficiency and throughput needed for hardware deployment, particularly when the resources are limited, without sacrificing accuracy.
no code implementations • 12 Apr 2022 • Mariam Rakka, Mohammed E. Fouda, Rouwaida Kanj, Fadi Kurdahi
Decision trees are considered one of the most powerful tools for data classification.
no code implementations • 10 Jan 2022 • Hsi-Hung Lu, Chung-An Shen, Mohammed E. Fouda, Ahmed M. Eltawil
Specifically, the proposed accelerator is based on a high-performance matrix multiplication array (MMA).
no code implementations • 13 Dec 2021 • Wenzhe Guo, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama
The results reveal that temporal truncation has a negative effect on the accuracy of classifying frame-based datasets, but leads to improvement in accuracy on dynamic-vision-sensor (DVS) recorded datasets.
no code implementations • 8 Sep 2021 • Kamilya Smagulova, Mohammed E. Fouda, Fadi Kurdahi, Khaled Salama, Ahmed Eltawil
The review covers different aspects of hardware and software realization of DNN accelerators, their present limitations, and future prospectives.
1 code implementation • 21 Nov 2020 • Melika Payvand, Mohammed E. Fouda, Fadi Kurdahi, Ahmed M. Eltawil, Emre O. Neftci
Recent breakthroughs in neuromorphic computing show that local forms of gradient descent learning are compatible with Spiking Neural Networks (SNNs) and synaptic plasticity.