11 citations · 26 across the 7 of their papers we have counts for
14 papers
Adversarial Attack by Limited Point Cloud Surface Modifications
Atrin Arya, Hanieh Naderi, Shohreh Kasaei
Recent research has revealed that the security of deep neural networks that directly process 3D point clouds to classify objects can be threatened by adversarial samples. Although…
CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search
Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Li Cheng +2
A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking resu…
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei +1
In parametric Bayesian learning, a prior is assumed on the parameter which determines the distribution of samples. In this setting, Minimum Excess Risk (MER) is defined as the…
Generating Unrestricted Adversarial Examples via Three Parameters
Hanieh Naderi, Leili Goli, Shohreh Kasaei
Deep neural networks have been shown to be vulnerable to adversarial examples deliberately constructed to misclassify victim models. As most adversarial examples have restricted th…
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer
Mahdi Ghorbani, Fahimeh Fooladgar, Shohreh Kasaei
Deep neural network architectures have attained remarkable improvements in scene understanding tasks. Utilizing an efficient model is one of the most important constraints for limi…
Adaptive Exploitation of Pre-trained Deep Convolutional Neural Networks for Robust Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
Due to the automatic feature extraction procedure via multi-layer nonlinear transformations, the deep learning-based visual trackers have recently achieved great success in challen…