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A Study and Comparison of Human and Deep Learning Recognition
  Performance Under Visual Distortions

A Study and Comparison of Human and Deep Learning Recognition Performance Under Visual Distortions

6 May 2017
Samuel F. Dodge
Lina Karam
    3DH
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Papers citing "A Study and Comparison of Human and Deep Learning Recognition Performance Under Visual Distortions"

15 / 65 papers shown
Title
Utilizing Network Properties to Detect Erroneous Inputs
Utilizing Network Properties to Detect Erroneous Inputs
Matt Gorbett
Nathaniel Blanchard
AAML
23
6
0
28 Feb 2020
CheXpedition: Investigating Generalization Challenges for Translation of
  Chest X-Ray Algorithms to the Clinical Setting
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting
Pranav Rajpurkar
Anirudh Joshi
Anuj Pareek
Phil Chen
Amirhossein Kiani
Jeremy Irvin
A. Ng
M. Lungren
LM&MA
27
49
0
26 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An
  Empirical Study
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study
David Mickisch
F. Assion
Florens Greßner
W. Günther
M. Motta
AAML
19
34
0
05 Feb 2020
A simple way to make neural networks robust against diverse image
  corruptions
A simple way to make neural networks robust against diverse image corruptions
E. Rusak
Lukas Schott
Roland S. Zimmermann
Julian Bitterwolf
Oliver Bringmann
Matthias Bethge
Wieland Brendel
21
64
0
16 Jan 2020
Angular Visual Hardness
Angular Visual Hardness
Beidi Chen
Weiyang Liu
Zhiding Yu
Jan Kautz
Anshumali Shrivastava
Animesh Garg
Anima Anandkumar
AAML
43
51
0
04 Dec 2019
Using learned optimizers to make models robust to input noise
Using learned optimizers to make models robust to input noise
Luke Metz
Niru Maheswaranathan
Jonathon Shlens
Jascha Narain Sohl-Dickstein
E. D. Cubuk
VLM
OOD
23
26
0
08 Jun 2019
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian
  Augmentation
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation
Raphael Gontijo-Lopes
Dong Yin
Ben Poole
Justin Gilmer
E. D. Cubuk
AAML
33
204
0
06 Jun 2019
Orthogonal Deep Neural Networks
Orthogonal Deep Neural Networks
Kui Jia
Shuai Li
Yuxin Wen
Tongliang Liu
Dacheng Tao
39
132
0
15 May 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
22
1,998
0
08 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Nic Ford
Justin Gilmer
Nicholas Carlini
E. D. Cubuk
AAML
36
318
0
29 Jan 2019
CIFAR10 to Compare Visual Recognition Performance between Deep Neural
  Networks and Humans
CIFAR10 to Compare Visual Recognition Performance between Deep Neural Networks and Humans
T. Ho-Phuoc
11
41
0
18 Nov 2018
Distortion Robust Image Classification using Deep Convolutional Neural
  Network with Discrete Cosine Transform
Distortion Robust Image Classification using Deep Convolutional Neural Network with Discrete Cosine Transform
Md Tahmid Hossain
S. Teng
Dengsheng Zhang
Suryani Lim
Guojun Lu
23
30
0
14 Nov 2018
Eigen-Distortions of Hierarchical Representations
Eigen-Distortions of Hierarchical Representations
Alexander Berardino
Johannes Ballé
Valero Laparra
Eero P. Simoncelli
46
69
0
06 Oct 2017
Comparing deep neural networks against humans: object recognition when
  the signal gets weaker
Comparing deep neural networks against humans: object recognition when the signal gets weaker
Robert Geirhos
David H. J. Janssen
Heiko H. Schutt
Jonas Rauber
Matthias Bethge
Felix Wichmann
22
242
0
21 Jun 2017
DeepCorrect: Correcting DNN models against Image Distortions
DeepCorrect: Correcting DNN models against Image Distortions
Tejas S. Borkar
Lina Karam
27
93
0
05 May 2017
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