85 citations · 149 across the 12 of their papers we have counts for
12 papers
Deep-URL: A Model-Aware Approach To Blind Deconvolution Based On Deep Unfolded Richardson-Lucy Network
Chirag Agarwal, Shahin Khobahi, Arindam Bose +2
The lack of interpretability in current deep learning models causes serious concerns as they are extensively used for various life-critical applications. Hence, it is of paramount…
Deep Radar Waveform Design for Efficient Automotive Radar Sensing
Shahin Khobahi, Arindam Bose, Mojtaba Soltanalian
In radar systems, unimodular (or constant-modulus) waveform design plays an important role in achieving better clutter/interference rejection, as well as a more accurate estimation…
Explaining image classifiers by removing input features using generative models
Chirag Agarwal, Anh Nguyen
Perturbation-based explanation methods often measure the contribution of an input feature to an image classifier's outputs by heuristically removing it via e.g. blurring, adding no…
Improving Adversarial Robustness by Encouraging Discriminative Features
Chirag Agarwal, Anh Nguyen, Dan Schonfeld
Deep neural networks (DNNs) have achieved state-of-the-art results in various pattern recognition tasks. However, they perform poorly on out-of-distribution adversarial examples i.…
An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks
Chirag Agarwal, Bo Dong, Dan Schonfeld +1
Deep Neural Networks(DNN) have excessively advanced the field of computer vision by achieving state of the art performance in various vision tasks. These results are not limited to…
Convolutional Neural Network Steganalysis's Application to Steganography
Mehdi Sharifzadeh, Chirag Agarwal, Mohammed Aloraini +1
This paper presents a novel approach to increase the performance bounds of image steganography under the criteria of minimizing distortion. The proposed approach utilizes a stegana…