no code implementations • 17 Apr 2024 • MohammadHossein AskariHemmat, Ahmadreza Jeddi, Reyhane Askari Hemmat, Ivan Lazarevich, Alexander Hoffman, Sudhakar Sah, Ehsan Saboori, Yvon Savaria, Jean-Pierre David
In this work, we investigate the generalization properties of quantized neural networks, a characteristic that has received little attention despite its implications on model performance.
no code implementations • 19 Sep 2023 • Saad Ashfaq, Alexander Hoffman, Saptarshi Mitra, Sudhakar Sah, MohammadHossein AskariHemmat, Ehsan Saboori
The proliferation of edge devices has unlocked unprecedented opportunities for deep learning model deployment in computer vision applications.
no code implementations • 18 Apr 2023 • Darshan C. Ganji, Saad Ashfaq, Ehsan Saboori, Sudhakar Sah, Saptarshi Mitra, MohammadHossein AskariHemmat, Alexander Hoffman, Ahmed Hassanien, Mathieu Léonardon
A lot of recent progress has been made in ultra low-bit quantization, promising significant improvements in latency, memory footprint and energy consumption on edge devices.
no code implementations • 18 Jul 2022 • Saad Ashfaq, MohammadHossein AskariHemmat, Sudhakar Sah, Ehsan Saboori, Olivier Mastropietro, Alexander Hoffman
Deep Learning has been one of the most disruptive technological advancements in recent times.
no code implementations • 24 Jun 2022 • MohammadHossein AskariHemmat, Reyhane Askari Hemmat, Alex Hoffman, Ivan Lazarevich, Ehsan Saboori, Olivier Mastropietro, Yvon Savaria, Jean-Pierre David
To confirm our analytical study, we performed an extensive list of experiments summarized in this paper in which we show that the regularization effects of quantization can be seen in various vision tasks and models, over various datasets.
no code implementations • 19 Dec 2021 • Martin Ferianc, Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Quentin Cappart
Neural networks (NNs) are making a large impact both on research and industry.
no code implementations • 11 Jan 2021 • Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Yasser Idris, Davis Sawyer, MohammadHossein AskariHemmat, Ghouthi Boukli Hacene
Designing deep learning-based solutions is becoming a race for training deeper models with a greater number of layers.
no code implementations • 1 Apr 2013 • Shafigh Parsazad, Ehsan Saboori, Amin Allahyar
In the most intrusion detection systems (IDS), a system tries to learn characteristics of different type of attacks by analyzing packets that sent or received in network.