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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

21 June 2017
Robert Geirhos
David H. J. Janssen
Heiko H. Schutt
Jonas Rauber
Matthias Bethge
Felix Wichmann
ArXivPDFHTML

Papers citing "Comparing deep neural networks against humans: object recognition when the signal gets weaker"

29 / 29 papers shown
Title
Bayesian Comparisons Between Representations
Bayesian Comparisons Between Representations
Heiko H. Schütt
FAtt
283
0
0
20 Feb 2025
Noise robust neural network architecture
Noise robust neural network architecture
Yunuo Xiong
Hongwei Xiong
27
1
0
16 May 2023
ExpNet: A unified network for Expert-Level Classification
ExpNet: A unified network for Expert-Level Classification
Junde Wu
Huihui Fang
Yehui Yang
Yu Zhang
Haoyi Xiong
Huazhu Fu
Yanwu Xu
35
0
0
29 Nov 2022
Virtual Underwater Datasets for Autonomous Inspections
Virtual Underwater Datasets for Autonomous Inspections
Ioannis Polymenis
M. Haroutunian
R. Norman
D. Trodden
19
7
0
13 Sep 2022
Enhancing Diffusion-Based Image Synthesis with Robust Classifier
  Guidance
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance
Bahjat Kawar
Roy Ganz
Michael Elad
DiffM
29
38
0
18 Aug 2022
Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor
  Perturbation
Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation
Wei Dai
Daniel Berleant
VLM
AAML
27
8
0
02 Mar 2022
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network
  Sensors and its Application in Process Control
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network Sensors and its Application in Process Control
J. Pulsipher
Luke D. J. Coutinho
Tyler A. Soderstrom
Victor M. Zavala
HAI
12
7
0
03 Feb 2022
Wiggling Weights to Improve the Robustness of Classifiers
Wiggling Weights to Improve the Robustness of Classifiers
Sadaf Gulshad
Ivan Sosnovik
A. Smeulders
OOD
30
0
0
18 Nov 2021
Deep Neural Models for color discrimination and color constancy
Deep Neural Models for color discrimination and color constancy
Alban Flachot
A. Akbarinia
Heiko H. Schutt
R. Fleming
Felix Wichmann
K. Gegenfurtner
19
2
0
28 Dec 2020
Truly shift-invariant convolutional neural networks
Truly shift-invariant convolutional neural networks
Anadi Chaman
Ivan Dokmanić
23
68
0
28 Nov 2020
Learning Loss for Test-Time Augmentation
Learning Loss for Test-Time Augmentation
Ildoo Kim
Younghoon Kim
Sungwoong Kim
OOD
26
91
0
22 Oct 2020
Seeing eye-to-eye? A comparison of object recognition performance in
  humans and deep convolutional neural networks under image manipulation
Seeing eye-to-eye? A comparison of object recognition performance in humans and deep convolutional neural networks under image manipulation
Leonard E. van Dyck
W. Gruber
27
3
0
13 Jul 2020
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans
  by measuring error consistency
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
Robert Geirhos
Kristof Meding
Felix Wichmann
19
117
0
30 Jun 2020
A fully recurrent feature extraction for single channel speech
  enhancement
A fully recurrent feature extraction for single channel speech enhancement
M. Shifas
Santelli Claudio
Vassilis Tsiaras
Y. Stylianou
11
2
0
09 Jun 2020
Deep Neural Network Based Real-time Kiwi Fruit Flower Detection in an
  Orchard Environment
Deep Neural Network Based Real-time Kiwi Fruit Flower Detection in an Orchard Environment
Jongyoon Lim
H. Ahn
Mahla Nejati
Jamie Bell
Henry Williams
B. MacDonald
14
18
0
08 Jun 2020
A Deeper Look at the Unsupervised Learning of Disentangled
  Representations in $β$-VAE from the Perspective of Core Object
  Recognition
A Deeper Look at the Unsupervised Learning of Disentangled Representations in βββ-VAE from the Perspective of Core Object Recognition
Harshvardhan Digvijay Sikka
OCL
OOD
BDL
DRL
27
1
0
25 Apr 2020
Anomaly Detection in Video Data Based on Probabilistic Latent Space
  Models
Anomaly Detection in Video Data Based on Probabilistic Latent Space Models
Giulia Slavic
Damian Campo
Mohamad Baydoun
P. Marín
David Martín
L. Marcenaro
C. Regazzoni
DRL
27
13
0
17 Mar 2020
Convolutional Neural Networks as a Model of the Visual System: Past,
  Present, and Future
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future
Grace W. Lindsay
MedIm
35
424
0
20 Jan 2020
Defective Convolutional Networks
Defective Convolutional Networks
Tiange Luo
Tianle Cai
Mengxiao Zhang
Siyu Chen
Di He
Liwei Wang
AAML
35
3
0
19 Nov 2019
Metamorphic Testing of a Deep Learning based Forecaster
Metamorphic Testing of a Deep Learning based Forecaster
Anurag Dwarakanath
Manish Ahuja
Sanjay Podder
Silja Vinu
Arijit Naskar
M. Koushik
AI4TS
16
9
0
13 Jul 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
Assessment of Faster R-CNN in Man-Machine collaborative search
Assessment of Faster R-CNN in Man-Machine collaborative search
Arturo Deza
A. Surana
Miguel P. Eckstein
OOD
26
7
0
04 Apr 2019
Distinguishing mirror from glass: A 'big data' approach to material
  perception
Distinguishing mirror from glass: A 'big data' approach to material perception
Hideki Tamura
Konrad E. Prokott
R. Fleming
OOD
AAML
24
9
0
05 Mar 2019
Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure
Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure
Been Kim
Emily Reif
Martin Wattenberg
Samy Bengio
Michael C. Mozer
39
30
0
04 Mar 2019
Robust neural circuit reconstruction from serial electron microscopy
  with convolutional recurrent networks
Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks
Drew Linsley
Junkyung Kim
D. Berson
Thomas Serre
3DV
35
17
0
28 Nov 2018
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
GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story
  Generation
GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story Generation
Taehyeong Kim
Min-Oh Heo
Seonil Son
Kyoung-Wha Park
Byoung-Tak Zhang
31
75
0
28 May 2018
Solving Bongard Problems with a Visual Language and Pragmatic Reasoning
Solving Bongard Problems with a Visual Language and Pragmatic Reasoning
Stefan Depeweg
Constantin Rothkopf
Frank Jakel
LRM
22
42
0
12 Apr 2018
PsyPhy: A Psychophysics Driven Evaluation Framework for Visual
  Recognition
PsyPhy: A Psychophysics Driven Evaluation Framework for Visual Recognition
Brandon RichardWebster
Samuel E. Anthony
Walter J. Scheirer
21
72
0
19 Nov 2016
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