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
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning M. Ziatdinov Yongtao Liu K. Kelley Rama K Vasudevan Sergei V. Kalinin AI4CE 47 49 0 30 May 2022
Rethinking Saliency Map: An Context-aware Perturbation Method to Explain EEG-based Deep Learning Model Hanqi Wang Xiaoguang Zhu Tao Chen Chengfang Li Liang Song FAtt 29 5 0 30 May 2022
How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann Lorenzo Noci Thomas Hofmann BDL AAML 82 8 0 27 May 2022
How explainable are adversarially-robust CNNs? Mehdi Nourelahi Lars Kotthoff Peijie Chen Anh Totti Nguyen AAML FAtt 29 8 0 25 May 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi Runa Eschenhagen Philipp Hennig BDL 42 12 0 20 May 2022
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 163 268 0 19 May 2022
Trading Positional Complexity vs. Deepness in Coordinate Networks Jianqiao Zheng Sameera Ramasinghe Xueqian Li Simon Lucey 31 18 0 18 May 2022
Norm-Scaling for Out-of-Distribution Detection Deepak Ravikumar Kaushik Roy OODD UQCV 24 2 0 06 May 2022
Multimodal Detection of Unknown Objects on Roads for Autonomous Driving Daniel Bogdoll Enrico Eisen Maximilian Nitsche Christin Scheib J. Marius Zöllner 25 12 0 03 May 2022
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study) Michael Weiss Paolo Tonella AAML 23 50 0 02 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 33 48 0 01 May 2022
Optimizing One-pixel Black-box Adversarial Attacks Tianxun Zhou Shubhanka Agrawal Prateek Manocha AAML MLAU 24 3 0 30 Apr 2022
A Closer Look at Branch Classifiers of Multi-exit Architectures Shaohui Lin Bo Ji Rongrong Ji Angela Yao 17 4 0 28 Apr 2022
Adversarial Fine-tune with Dynamically Regulated Adversary Peng-Fei Hou Ming Zhou Jie Han Petr Musílek Xingyu Li AAML 31 3 0 28 Apr 2022
Learning by Erasing: Conditional Entropy based Transferable Out-Of-Distribution Detection Meng Xing Zhiyong Feng Yong Su Changjae Oh OODD 23 3 0 23 Apr 2022
Exploring Hidden Semantics in Neural Networks with Symbolic Regression Yuanzhen Luo Qiang Lu Xilei Hu Jake Luo Zhiguang Wang 26 0 0 22 Apr 2022
Patch-wise Contrastive Style Learning for Instagram Filter Removal Furkan Kinli B. Özcan Mustafa Furkan Kıraç 22 7 0 15 Apr 2022
Out-of-Distribution Detection with Deep Nearest Neighbors Yiyou Sun Yifei Ming Xiaojin Zhu Yixuan Li OODD 19 494 0 13 Apr 2022
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates Alina Roitberg Kunyu Peng David Schneider Kailun Yang Marios Koulakis Manuel Martínez Rainer Stiefelhagen UQCV 30 9 0 10 Apr 2022
Core Risk Minimization using Salient ImageNet Sahil Singla Mazda Moayeri S. Feizi 38 14 0 28 Mar 2022
A Systematic Survey of Attack Detection and Prevention in Connected and Autonomous Vehicles Trupil Limbasiya Ko Zheng Teng Sudipta Chattopadhyay Jianying Zhou 23 48 0 27 Mar 2022
Learning Confidence for Transformer-based Neural Machine Translation Yu Lu Jiali Zeng Jiajun Zhang Shuangzhi Wu Mu Li 49 9 0 22 Mar 2022
Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral Images Sam L. Polk Kangning Cui Aland H. Y. Chan David A. Coomes R. Plemmons James M. Murphy DiffM 19 8 0 18 Mar 2022
Visualizing Global Explanations of Point Cloud DNNs Hanxiao Tan 3DPC 50 7 0 17 Mar 2022
Confidence Calibration for Intent Detection via Hyperspherical Space and Rebalanced Accuracy-Uncertainty Loss Yantao Gong Cao Liu Fan Yang Xunliang Cai Guanglu Wan Jiansong Chen Weipeng Zhang Houfeng Wang UQCV 24 2 0 17 Mar 2022
A Continual Learning Framework for Adaptive Defect Classification and Inspection Wenbo Sun Raed Al Kontar Judy Jin Tzyy-Shuh Chang 23 10 0 16 Mar 2022
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space Poulami Sinhamahapatra Rajat Koner Karsten Roscher Stephan Günnemann OODD 11 5 0 16 Mar 2022
Towards understanding deep learning with the natural clustering prior Simon Carbonnelle 25 0 0 15 Mar 2022
Learning Discriminative Representations and Decision Boundaries for Open Intent Detection Hanlei Zhang Huan Xu Shaojie Zhao Qianrui Zhou 35 18 0 11 Mar 2022
Attacks as Defenses: Designing Robust Audio CAPTCHAs Using Attacks on Automatic Speech Recognition Systems H. Abdullah Aditya Karlekar S. Prasad Muhammad Sajidur Rahman Logan Blue L. A. Bauer Vincent Bindschaedler Patrick Traynor AAML 29 3 0 10 Mar 2022
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 41 21 0 09 Mar 2022
How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? Yifei Ming Yiyou Sun Ousmane Amadou Dia Yixuan Li OODD 26 96 0 08 Mar 2022
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors Wen Wu Chuxu Zhang Xixin Wu P. Woodland 48 14 0 08 Mar 2022
Adversarial Texture for Fooling Person Detectors in the Physical World Zhan Hu Siyuan Huang Xiaopei Zhu Gang Hua Bo Zhang Xiaolin Hu AAML 17 104 0 07 Mar 2022
Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection Yibo Zhou OODD 19 51 0 04 Mar 2022
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks Dmitrii Usynin Daniel Rueckert Georgios Kaissis SILM AAML 36 17 0 01 Mar 2022
Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data Yancheng Pan Fan Xie Huijing Zhao CVBM 36 7 0 01 Mar 2022
Testing Deep Learning Models: A First Comparative Study of Multiple Testing Techniques M. K. Ahuja A. Gotlieb Helge Spieker AAML 19 4 0 24 Feb 2022
Fine-grained TLS services classification with reject option Jan Luxemburk T. Čejka 24 32 0 24 Feb 2022
Calibrated Learning to Defer with One-vs-All Classifiers Rajeev Verma Eric Nalisnick 26 43 0 08 Feb 2022
Attacking c-MARL More Effectively: A Data Driven Approach Nhan H. Pham Lam M. Nguyen Jie Chen Hoang Thanh Lam Subhro Das Tsui-Wei Weng AAML 43 2 0 07 Feb 2022
Training OOD Detectors in their Natural Habitats Julian Katz-Samuels Julia B. Nakhleh Robert D. Nowak Yixuan Li OODD 27 90 0 07 Feb 2022
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network Nikita Kotelevskii A. Artemenkov Kirill Fedyanin Fedor Noskov Alexander Fishkov Artem Shelmanov Artem Vazhentsev Aleksandr Petiushko Maxim Panov UQCV BDL 56 26 0 07 Feb 2022
Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets Guy Hacohen Avihu Dekel D. Weinshall 134 116 0 06 Feb 2022
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks Lukas Struppek Dominik Hintersdorf Antonio De Almeida Correia Antonia Adler Kristian Kersting MIACV 63 62 0 28 Jan 2022
Variational Model Inversion Attacks Kuan-Chieh Wang Yanzhe Fu Ke Li Ashish Khisti R. Zemel Alireza Makhzani MIACV 30 95 0 26 Jan 2022
Self-Supervised Anomaly Detection by Self-Distillation and Negative Sampling Nima Rafiee Rahil Gholamipoorfard Nikolas Adaloglou Simon Jaxy Julius Ramakers M. Kollmann OODD 25 8 0 17 Jan 2022
Robust uncertainty estimates with out-of-distribution pseudo-inputs training Pierre Segonne Yevgen Zainchkovskyy Søren Hauberg UQCV OOD 13 1 0 15 Jan 2022
Evaluation of Neural Networks Defenses and Attacks using NDCG and Reciprocal Rank Metrics Haya Brama L. Dery Tal Grinshpoun AAML 19 7 0 10 Jan 2022
Problem-dependent attention and effort in neural networks with applications to image resolution and model selection Chris Rohlfs 34 4 0 05 Jan 2022