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"

33 / 33 papers shown

Title
FADEL: Uncertainty-aware Fake Audio Detection with Evidential Deep Learning Ju Yeon Kang J. Yoon Semin Kim Min Hyun Han Nam Soo Kim 76 0 0 22 Apr 2025
CADRef: Robust Out-of-Distribution Detection via Class-Aware Decoupled Relative Feature Leveraging Zhiwei Ling Yachen Chang Hailiang Zhao Xinkui Zhao Kingsum Chow Shuiguang Deng OODD 126 0 0 01 Mar 2025
Out-of-Distribution Detection using Synthetic Data Generation Momin Abbas Muneeza Azmat R. Horesh Mikhail Yurochkin 157 1 0 05 Feb 2025
Killing it with Zero-Shot: Adversarially Robust Novelty Detection Hossein Mirzaei Mohammad Jafari Hamid Reza Dehbashi Zeinab Sadat Taghavi Mohammad Sabokrou M. Rohban 106 2 0 28 Jan 2025
Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach Nicolas Atienza Christophe Labreuche Johanne Cohen Michele Sebag OODD AAML 390 0 0 20 Jan 2025
Distribution Shifts at Scale: Out-of-distribution Detection in Earth Observation Burak Ekim G. Tadesse Caleb Robinson G. Q. Hacheme Michael Schmitt Rahul Dodhia J. L. Ferres OODD 169 1 0 18 Dec 2024
PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image Classification Sara Pohland Claire Tomlin UQCV 172 1 0 22 Nov 2024
Going Beyond Conventional OOD Detection Sudarshan Regmi OODD 101 1 0 16 Nov 2024
Deep Active Learning in the Open World Tian Xie Jifan Zhang Haoyue Bai R. Nowak VLM 383 3 0 10 Nov 2024
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 90 1 0 30 Oct 2024
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers Lam Nguyen Tung Steven Cho Xiaoning Du Neelofar Neelofar Valerio Terragni Stefano Ruberto Aldeida Aleti 466 2 0 30 Oct 2024
Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks Hunmin Yang Jongoh Jeong Kuk-Jin Yoon AAML VLM 123 5 0 30 Jul 2024
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu Aditya Singh Yijiang Li Haohan Wang AAML ViT 95 1 0 15 Mar 2024
Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy Will LeVine Benjamin Pikus Jacob Phillips Berk Norman Fernando Amat Gil Sean Hendryx OODD 131 1 0 22 Jan 2024
The Representational Status of Deep Learning Models Eamon Duede 77 0 0 21 Mar 2023
Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation Qilong Zhang Chaoning Zhang Chaoning Zhang Chaoqun Li Xuanhan Wang Jingkuan Song Lianli Gao AAML 102 21 0 09 Mar 2022
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 94 73 0 07 Aug 2020
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness Mohammadamin Tavakoli Forest Agostinelli Pierre Baldi AAML FAtt 177 39 0 16 Jun 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 112 83 0 17 Mar 2020
Defending against Backdoor Attack on Deep Neural Networks Kaidi Xu Sijia Liu Pin-Yu Chen Pu Zhao Xinyu Lin Xue Lin AAML 61 49 0 26 Feb 2020
Deep Reinforcement Learning for De-Novo Drug Design Mariya Popova Olexandr Isayev Alexander Tropsha 85 1,031 0 29 Nov 2017
DeepCorrect: Correcting DNN models against Image Distortions Tejas S. Borkar Lina Karam 82 93 0 05 May 2017
Robustness to Adversarial Examples through an Ensemble of Specialists Mahdieh Abbasi Christian Gagné AAML 79 109 0 22 Feb 2017
Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics Xin Li Fuxin Li GAN AAML 110 365 0 22 Dec 2016
Microstructure Representation and Reconstruction of Heterogeneous Materials via Deep Belief Network for Computational Material Design Ruijin Cang Yaopengxiao Xu Shaohua Chen Yongming Liu Yang Jiao Max Yi Ren AI4CE 3DV 68 156 0 22 Dec 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 231 8,336 0 06 Nov 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 465 43,658 0 17 Sep 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,547 0 01 Sep 2014
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 274 14,711 0 20 Jun 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,927 1 21 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,295 0 20 Dec 2013
Deep Generative Stochastic Networks Trainable by Backprop Yoshua Bengio Eric Thibodeau-Laufer Guillaume Alain J. Yosinski BDL 128 396 0 05 Jun 2013