71 citations · 183 across the 15 of their papers we have counts for
17 papers
AttendNets: Tiny Deep Image Recognition Neural Networks for the Edge via Visual Attention Condensers
Alexander Wong, Mahmoud Famouri, Mohammad Javad Shafiee
While significant advances in deep learning has resulted in state-of-the-art performance across a large number of complex visual perception tasks, the widespread deployment of deep…
Vulnerability Under Adversarial Machine Learning: Bias or Variance?
Hossein Aboutalebi, Mohammad Javad Shafiee, Michelle Karg +2
Prior studies have unveiled the vulnerability of the deep neural networks in the context of adversarial machine learning, leading to great recent attention into this area. One inte…
Deep Neural Network Perception Models and Robust Autonomous Driving Systems
Mohammad Javad Shafiee, Ahmadreza Jeddi, Amir Nazemi +2
This paper analyzes the robustness of deep learning models in autonomous driving applications and discusses the practical solutions to address that.
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness
Ahmadreza Jeddi, Mohammad Javad Shafiee, Michelle Karg +2
While deep neural networks have been achieving state-of-the-art performance across a wide variety of applications, their vulnerability to adversarial attacks limits their widesprea…
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms
Zhong Qiu Lin, Mohammad Javad Shafiee, Stanislav Bochkarev +3
There has been a significant surge of interest recently around the concept of explainable artificial intelligence (XAI), where the goal is to produce an interpretation for a decisi…
State of Compact Architecture Search For Deep Neural Networks
Mohammad Javad Shafiee, Andrew Hryniowski, Francis Li +2
The design of compact deep neural networks is a crucial task to enable widespread adoption of deep neural networks in the real-world, particularly for edge and mobile scenarios. Du…