55 citations · 328 across the 36 of their papers we have counts for
6 papers · 1 filter
Robustification of Segmentation Models Against Adversarial Perturbations In Medical Imaging
Hanwool Park, Amirhossein Bayat, Mohammad Sabokrou +2
This paper presents a novel yet efficient defense framework for segmentation models against adversarial attacks in medical imaging. In contrary to the defense methods against adver…
G2D: Generate to Detect Anomaly
Masoud Pourreza, Bahram Mohammadi, Mostafa Khaki +3
In this paper, we propose a novel method for irregularity detection. Previous researches solve this problem as a One-Class Classification (OCC) task where they train a reference mo…
Conditional Classification: A Solution for Computational Energy Reduction
Ali Mirzaeian, Sai Manoj, Ashkan Vakil +2
Deep convolutional neural networks have shown high efficiency in computer visions and other applications. However, with the increase in the depth of the networks, the computational…
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks
Ali Mirzaeian, Jana Kosecka, Houman Homayoun +2
This paper proposes an ensemble learning model that is resistant to adversarial attacks. To build resilience, we introduced a training process where each member learns a radically…
Deep-HR: Fast Heart Rate Estimation from Face Video Under Realistic Conditions
Mohammad Sabokrou, Masoud Pourreza, Xiaobai Li +2
This paper presents a novel method for remote heart rate (HR) estimation. Recent studies have proved that blood pumping by the heart is highly correlated to the intense color of fa…
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks
Farnaz Behnia, Ali Mirzaeian, Mohammad Sabokrou +6
In this paper, we propose Code-Bridged Classifier (CBC), a framework for making a Convolutional Neural Network (CNNs) robust against adversarial attacks without increasing or even…