Defending Against Adversarial Iris Examples Using Wavelet Decomposition

8 August 2019

Papers citing "Defending Against Adversarial Iris Examples Using Wavelet Decomposition"

31 / 31 papers shown

Title
Adversarial Examples to Fool Iris Recognition Systems Sobhan Soleymani Ali Dabouei J. Dawson Nasser M. Nasrabadi GAN AAML 46 16 0 21 Jun 2019
Learning to Authenticate with Deep Multibiometric Hashing and Neural Network Decoding Veeru Talreja Sobhan Soleymani Matthew C. Valenti Nasser M. Nasrabadi 22 15 0 11 Feb 2019
Using Deep Cross Modal Hashing and Error Correcting Codes for Improving the Efficiency of Attribute Guided Facial Image Retrieval Veeru Talreja Fariborz Taherkhani Matthew C. Valenti Nasser M. Nasrabadi 46 15 0 11 Feb 2019
Fast Geometrically-Perturbed Adversarial Faces Ali Dabouei Sobhan Soleymani J. Dawson Nasser M. Nasrabadi CVBM AAML 47 65 0 24 Sep 2018
Prosodic-Enhanced Siamese Convolutional Neural Networks for Cross-Device Text-Independent Speaker Verification Sobhan Soleymani Ali Dabouei Seyed Mehdi Iranmanesh Hadi Kazemi J. Dawson Nasser M. Nasrabadi 33 18 0 31 Jul 2018
Multi-Level Feature Abstraction from Convolutional Neural Networks for Multimodal Biometric Identification Sobhan Soleymani Ali Dabouei Hadi Kazemi J. Dawson Nasser M. Nasrabadi CVBM 60 70 0 03 Jul 2018
Generalized Bilinear Deep Convolutional Neural Networks for Multimodal Biometric Identification Sobhan Soleymani A. Torfi J. Dawson Nasser M. Nasrabadi 113 29 0 03 Jul 2018
A Deep Face Identification Network Enhanced by Facial Attributes Prediction Fariborz Taherkhani Nasser M. Nasrabadi J. Dawson CVBM 67 48 0 20 Apr 2018
Defending against Adversarial Images using Basis Functions Transformations Uri Shaham J. Garritano Yutaro Yamada Ethan Weinberger A. Cloninger Xiuyuan Cheng Kelly P. Stanton Y. Kluger AAML 51 57 0 28 Mar 2018
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 94 1,622 0 19 Dec 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 110 790 0 30 Oct 2017
Multibiometric Secure System Based on Deep Learning Veeru Talreja Matthew C. Valenti Nasser M. Nasrabadi 33 67 0 07 Aug 2017
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 103 171 0 08 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 307 12,069 0 19 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 46 1,208 0 25 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 126 1,864 0 20 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,725 0 19 May 2017
Robustness to Adversarial Examples through an Ensemble of Specialists Mahdieh Abbasi Christian Gagné AAML 79 109 0 22 Feb 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 76 714 0 21 Feb 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 318 1,873 0 03 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 540 5,897 0 08 Jul 2016
Adversarial Diversity and Hard Positive Generation Andras Rozsa Ethan M. Rudd Terrance E. Boult 81 257 0 05 May 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 110 3,962 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 151 4,897 0 14 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 108 3,072 0 14 Nov 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.8K 77,196 0 18 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 468 43,658 0 17 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 275 14,927 1 21 Dec 2013
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 163 2,119 0 21 Dec 2013