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1505.06795
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An Empirical Evaluation of Current Convolutional Architectures' Ability to Manage Nuisance Location and Scale Variability
26 May 2015
Nikolaos Karianakis
Jingming Dong
Stefano Soatto
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Papers citing
"An Empirical Evaluation of Current Convolutional Architectures' Ability to Manage Nuisance Location and Scale Variability"
5 / 5 papers shown
Title
Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack Detection
Renu Sharma
Redwan Sony
Arun Ross
AAML
18
3
0
21 Nov 2023
With Friends Like These, Who Needs Adversaries?
Saumya Jetley
Nicholas A. Lord
Philip Torr
AAML
18
70
0
11 Jul 2018
Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems
Adam Kortylewski
Bernhard Egger
Andreas C. Schneider
Thomas Gerig
Andreas Morel-Forster
T. Vetter
CVBM
25
71
0
05 Dec 2017
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches
E. Rodner
Marcel Simon
Robert B. Fisher
Joachim Denzler
17
39
0
21 Oct 2016
MatConvNet - Convolutional Neural Networks for MATLAB
Andrea Vedaldi
Karel Lenc
183
2,946
0
15 Dec 2014
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