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

5 December 2014

Jeff Clune

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

50 / 1,401 papers shown

Title
A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity Peijie Yin Hong Qiao Wei Wu Lu Qi Yinlin Li Shanlin Zhong Bo-Wen Zhang 11 8 0 25 Mar 2016
Harnessing Deep Neural Networks with Logic Rules Zhiting Hu Xuezhe Ma Zhengzhong Liu Eduard H. Hovy Eric Xing AI4CE NAI 18 610 0 21 Mar 2016
A Survey of Stealth Malware: Attacks, Mitigation Measures, and Steps Toward Autonomous Open World Solutions Ethan M. Rudd Andras Rozsa Manuel Günther Terrance E. Boult 20 154 0 19 Mar 2016
Suppressing the Unusual: towards Robust CNNs using Symmetric Activation Functions Qiyang Zhao Lewis D. Griffin AAML 6 28 0 16 Mar 2016
Turing learning: a metric-free approach to inferring behavior and its application to swarms Wei Li Melvin Gauci R. Groß 16 55 0 15 Mar 2016
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks Anh Totti Nguyen J. Yosinski Jeff Clune 28 324 0 11 Feb 2016
The Role of Typicality in Object Classification: Improving The Generalization Capacity of Convolutional Neural Networks Babak Saleh Ahmed Elgammal J. Feldman 19 16 0 09 Feb 2016
Graying the black box: Understanding DQNs Tom Zahavy Nir Ben-Zrihem Shie Mannor 13 262 0 08 Feb 2016
Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization Alexander Ororbia C. Lee Giles Daniel Kifer OOD 16 24 0 26 Jan 2016
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision Suraj Srinivas Ravi Kiran Sarvadevabhatla Konda Reddy Mopuri N. Prabhu S. Kruthiventi R. Venkatesh Babu OOD 35 215 0 25 Jan 2016
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images Aravindh Mahendran Andrea Vedaldi FAtt 11 531 0 07 Dec 2015
Thinking Required K. Rocki AI4CE 28 0 0 07 Dec 2015
Predicting and visualizing psychological attributions with a deep neural network Edward Grant Stephan Sahm M. Zabihi Marcel van Gerven FAtt CVBM 12 2 0 04 Dec 2015
Loss Functions for Neural Networks for Image Processing Hang Zhao Orazio Gallo I. Frosio Jan Kautz SupR 14 277 0 28 Nov 2015
Convergent Learning: Do different neural networks learn the same representations? Yixuan Li J. Yosinski Jeff Clune Hod Lipson J. Hopcroft SSL 48 355 0 24 Nov 2015
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 19 3,934 0 24 Nov 2015
What Happened to My Dog in That Network: Unraveling Top-down Generators in Convolutional Neural Networks Patrick W. Gallagher Shuai Tang Zhuowen Tu 10 5 0 23 Nov 2015
Auxiliary Image Regularization for Deep CNNs with Noisy Labels S. Azadi Jiashi Feng Stefanie Jegelka Trevor Darrell NoLa 19 89 0 22 Nov 2015
On the energy landscape of deep networks Pratik Chaudhari Stefano Soatto ODL 43 27 0 20 Nov 2015
Deep Manifold Traversal: Changing Labels with Convolutional Features Jacob R. Gardner P. Upchurch Matt J. Kusner Yixuan Li Kilian Q. Weinberger Kavita Bala J. Hopcroft 34 65 0 19 Nov 2015
A Unified Gradient Regularization Family for Adversarial Examples Chunchuan Lyu Kaizhu Huang Hai-Ning Liang AAML 13 207 0 19 Nov 2015
Manifold Regularized Deep Neural Networks using Adversarial Examples Taehoon Lee Minsuk Choi Sungroh Yoon AAML GAN OOD 21 14 0 19 Nov 2015
Robust Convolutional Neural Networks under Adversarial Noise Jonghoon Jin Aysegül Dündar Eugenio Culurciello 29 77 0 19 Nov 2015
Foveation-based Mechanisms Alleviate Adversarial Examples Yan Luo Xavier Boix Gemma Roig T. Poggio Qi Zhao AAML 21 170 0 19 Nov 2015
Towards Open Set Deep Networks Abhijit Bendale Terrance Boult BDL EDL 17 1,400 0 19 Nov 2015
Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization Uri Shaham Yutaro Yamada S. Negahban AAML 27 74 0 17 Nov 2015
Adversarial Manipulation of Deep Representations S. Sabour Yanshuai Cao Fartash Faghri David J. Fleet GAN AAML 30 286 0 16 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 40 4,852 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 20 3,051 0 14 Nov 2015
Analyzing Stability of Convolutional Neural Networks in the Frequency Domain E. J. Heravi H. H. Aghdam D. Puig FAtt 8 3 0 10 Nov 2015
Visual Language Modeling on CNN Image Representations Hiroharu Kato Tatsuya Harada FAtt 25 7 0 09 Nov 2015
Confusing Deep Convolution Networks by Relabelling Leigh Robinson Benjamin Graham 16 3 0 23 Oct 2015
Exploring the Space of Adversarial Images Pedro Tabacof Eduardo Valle AAML 20 191 0 19 Oct 2015
A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas Haohan Wang Bhiksha Raj AI4TS 27 34 0 16 Oct 2015
Improving Back-Propagation by Adding an Adversarial Gradient Arild Nøkland AAML 32 32 0 14 Oct 2015
Learning a Discriminative Model for the Perception of Realism in Composite Images Jun-Yan Zhu Philipp Krahenbuhl Eli Shechtman Alexei A. Efros SSL GAN 21 140 0 02 Oct 2015
Evasion and Hardening of Tree Ensemble Classifiers Alex Kantchelian J. D. Tygar A. Joseph AAML 20 206 0 25 Sep 2015
Evaluating the visualization of what a Deep Neural Network has learned Wojciech Samek Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller XAI 74 1,180 0 21 Sep 2015
The SP theory of intelligence: distinctive features and advantages J. G. Wolff 27 31 0 17 Aug 2015
Deep Learning and Music Adversaries Corey Kereliuk Bob L. T. Sturm J. Larsen AAML 16 136 0 16 Jul 2015
Understanding Neural Networks Through Deep Visualization J. Yosinski Jeff Clune Anh Totti Nguyen Thomas J. Fuchs Hod Lipson FAtt AI4CE 64 1,864 0 22 Jun 2015
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop Feng Yu Ari Seff Yinda Zhang Shuran Song Thomas Funkhouser Jianxiong Xiao 20 2,309 0 10 Jun 2015
Reflection Invariance: an important consideration of image orientation Craig Henderson E. Izquierdo 14 2 0 08 Jun 2015
Visualizing and Understanding Neural Models in NLP Jiwei Li Xinlei Chen Eduard H. Hovy Dan Jurafsky MILM FAtt 32 701 0 02 Jun 2015
An Empirical Evaluation of Current Convolutional Architectures' Ability to Manage Nuisance Location and Scale Variability Nikolaos Karianakis Jingming Dong Stefano Soatto 30 15 0 26 May 2015
Image Reconstruction from Bag-of-Visual-Words Hiroharu Kato Tatsuya Harada 65 84 0 19 May 2015
What Do Deep CNNs Learn About Objects? Xingchao Peng Baochen Sun Karim Ali Kate Saenko 3DPC 18 3 0 09 Apr 2015
Analysis of classifiers' robustness to adversarial perturbations Alhussein Fawzi Omar Fawzi P. Frossard AAML 35 361 0 09 Feb 2015
Why does Deep Learning work? - A perspective from Group Theory Arnab Paul Suresh Venkatasubramanian 37 21 0 20 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 36 18,808 0 20 Dec 2014