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Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

Computer Vision and Pattern Recognition (CVPR), 2014

5 December 2014

Jeff Clune

Papers citing "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"

50 / 1,455 papers shown

Title
Butterfly Effect: Bidirectional Control of Classification Performance by Small Additive Perturbation Y. Yoo Seonguk Park Junyoung Choi Sangdoo Yun Nojun Kwak AAML 158 4 0 27 Nov 2017
Context Augmentation for Convolutional Neural Networks Aysegül Dündar Ignacio Garcia Dorado 107 5 0 22 Nov 2017
How morphological development can guide evolution Sam Kriegman Nick Cheney Josh Bongard 301 100 0 20 Nov 2017
Adversarial Attacks Beyond the Image Space Fangyin Wei Chenxi Liu Yu-Siang Wang Weichao Qiu Lingxi Xie Yu-Wing Tai Chi-Keung Tang Alan Yuille AAML 386 158 0 20 Nov 2017
Defense against Universal Adversarial Perturbations Naveed Akhtar Jian Liu Lin Wang AAML 293 212 0 16 Nov 2017
Interpreting Deep Visual Representations via Network Dissection Bolei Zhou David Bau A. Oliva Antonio Torralba FAtt MILM 209 350 0 15 Nov 2017
Sound Event Detection in Synthetic Audio: Analysis of the DCASE 2016 Task Results G. Lafay Emmanouil Benetos Mathieu Lagrange 76 23 0 15 Nov 2017
Towards Interpretable R-CNN by Unfolding Latent Structures Tianfu Wu Wei Sun Xilai Li Xi Song Yangqiu Song ObjD 150 20 0 14 Nov 2017
Applications of Deep Learning and Reinforcement Learning to Biological Data M. S. M. Mahmud M. S. Kaiser Amir Hussain S. Vassanelli OffRL AI4CE 131 685 0 10 Nov 2017
Performance Evaluation of Deep Learning Tools in Docker Containers Pengfei Xu Shaoshuai Shi Xiaowen Chu 109 47 0 09 Nov 2017
A Saak Transform Approach to Efficient, Scalable and Robust Handwritten Digits RecognitionPicture Coding Symposium (PCS), 2017 Yueru Chen Zhuwei Xu Shanshan Cai Yujian Lang C.-C. Jay Kuo 95 35 0 29 Oct 2017
Certifying Some Distributional Robustness with Principled Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2017 Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 401 910 0 29 Oct 2017
Class Correlation affects Single Object Localization using Pre-trained ConvNets P. H. Vardhan Kunal Sekhri Dipan K. Pal Marios Savvides 87 0 0 26 Oct 2017
One pixel attack for fooling deep neural networksIEEE Transactions on Evolutionary Computation (IEEE TEVC), 2017 Jiawei Su Danilo Vasconcellos Vargas Kouichi Sakurai AAML 543 2,483 0 24 Oct 2017
Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks Matthew Ragoza Lillian Turner D. Koes 70 16 0 20 Oct 2017
Do Convolutional Neural Networks Learn Class Hierarchy? B. Alsallakh Amin Jourabloo Mao Ye Xiaoming Liu Liu Ren 241 224 0 17 Oct 2017
On Data-Driven Saak Transform C.-C. Jay Kuo Yueru Chen AI4TS 171 95 0 11 Oct 2017
Lung Cancer Screening Using Adaptive Memory-Augmented Recurrent Networks Aryan Mobiny S. Moulik H. Nguyen 93 13 0 11 Oct 2017
Standard detectors aren't (currently) fooled by physical adversarial stop signs Jiajun Lu Hussein Sibai Evan Fabry David A. Forsyth AAML 178 60 0 09 Oct 2017
Eigen-Distortions of Hierarchical Representations Alexander Berardino Johannes Ballé Valero Laparra Eero P. Simoncelli 155 77 0 06 Oct 2017
Improving image generative models with human interactions Andrew Kyle Lampinen David R. So Douglas Eck Fred Bertsch GAN 66 3 0 29 Sep 2017
Distance-based Confidence Score for Neural Network Classifiers Amit Mandelbaum D. Weinshall UQCV 176 116 0 28 Sep 2017
Fooling Vision and Language Models Despite Localization and Attention Mechanism Xiaojun Xu Xinyun Chen Chang-rui Liu Anna Rohrbach Trevor Darrell Basel Alomair AAML 212 41 0 25 Sep 2017
Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy Search Rémi Pautrat Konstantinos Chatzilygeroudis Jean-Baptiste Mouret 154 44 0 20 Sep 2017
ZhuSuan: A Library for Bayesian Deep Learning Jiaxin Shi Jianfei Chen Jun Zhu Shengyang Sun Yucen Luo Yihong Gu Yuhao Zhou UQCV BDL 131 43 0 18 Sep 2017
Denoising Autoencoders for Overgeneralization in Neural Networks G. Spigler UQCV AI4CE 124 32 0 14 Sep 2017
Can Deep Neural Networks Match the Related Objects?: A Survey on ImageNet-trained Classification Models Han S. Lee Heechul Jung Alex A. Agarwal Junmo Kim 144 6 0 12 Sep 2017
Investigating how well contextual features are captured by bi-directional recurrent neural network models Kushal Chawla Sunil Kumar Sahu Ashish Anand 95 2 0 03 Sep 2017
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars Yuchi Tian Kexin Pei Suman Jana Baishakhi Ray AAML 210 1,429 0 28 Aug 2017
On denoising autoencoders trained to minimise binary cross-entropy Antonia Creswell Kai Arulkumaran Anil A. Bharath 146 77 0 28 Aug 2017
What does 2D geometric information really tell us about 3D face shape? Anil Bas W. Smith 3DH CVBM 3DV 191 24 0 22 Aug 2017
Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples Yinpeng Dong Hang Su Jun Zhu Fan Bao AAML 223 132 0 18 Aug 2017
SMAUG: Secure Mobile Authentication Using Gestures C. Gorke Frederik Armknecht 76 0 0 16 Aug 2017
Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API Hossein Hosseini Baicen Xiao Andrew Clark Radha Poovendran AAML 150 25 0 14 Aug 2017
Adversarial Robustness: Softmax versus Openmax Andras Rozsa Manuel Günther Terrance E. Boult AAML 119 37 0 05 Aug 2017
Capacity limitations of visual search in deep convolutional neural networks E. Põder VLM 92 7 0 31 Jul 2017
Deep Feature Consistent Deep Image Transformations: Downscaling, Decolorization and HDR Tone Mapping Xianxu Hou Jiang Duan Guoping Qiu 100 33 0 29 Jul 2017
Photographic Image Synthesis with Cascaded Refinement Networks Qifeng Chen V. Koltun 256 983 0 28 Jul 2017
Confidence estimation in Deep Neural networks via density modelling Akshayvarun Subramanya Suraj Srinivas R. Venkatesh Babu 94 52 0 21 Jul 2017
Efficient Defenses Against Adversarial Attacks Valentina Zantedeschi Maria-Irina Nicolae Ambrish Rawat AAML 258 311 0 21 Jul 2017
Fast Feature Fool: A data independent approach to universal adversarial perturbations Konda Reddy Mopuri Utsav Garg R. Venkatesh Babu AAML 211 220 0 18 Jul 2017
NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles Jiajun Lu Hussein Sibai Evan Fabry David A. Forsyth AAML 200 288 0 12 Jul 2017
Learning in High-Dimensional Multimedia Data: The State of the Art Lianli Gao Jingkuan Song Xingyi Liu Junming Shao Jiajun Liu Jie Shao 108 125 0 10 Jul 2017
UPSET and ANGRI : Breaking High Performance Image Classifiers Sayantan Sarkar Ankan Bansal U. Mahbub Rama Chellappa AAML 123 111 0 04 Jul 2017
Using deep learning to reveal the neural code for images in primary visual cortex W. Kindel Elijah D. Christensen J. Zylberberg FAtt 120 29 0 19 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 1.2K 13,593 0 19 Jun 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini Basel Alomair AAML 167 241 0 15 Jun 2017
Reinforcement Learning with Budget-Constrained Nonparametric Function Approximation for Opportunistic Spectrum Access Theodoros Tsiligkaridis David Romero 117 2 0 14 Jun 2017
When Image Denoising Meets High-Level Vision Tasks: A Deep Learning ApproachInternational Joint Conference on Artificial Intelligence (IJCAI), 2017 Ding Liu Bihan Wen Xianming Liu Zhangyang Wang Thomas S. Huang VLM 196 235 0 14 Jun 2017
Confident Multiple Choice LearningInternational Conference on Machine Learning (ICML), 2017 Kimin Lee Changho Hwang KyoungSoo Park Jinwoo Shin 134 51 0 12 Jun 2017