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Statistical theory for image classification using deep convolutional
  neural networks with cross-entropy loss under the hierarchical max-pooling
  model

Statistical theory for image classification using deep convolutional neural networks with cross-entropy loss under the hierarchical max-pooling model

27 November 2020
Michael Kohler
S. Langer
ArXivPDFHTML

Papers citing "Statistical theory for image classification using deep convolutional neural networks with cross-entropy loss under the hierarchical max-pooling model"

3 / 3 papers shown
Title
Convergence rates of deep ReLU networks for multiclass classification
Convergence rates of deep ReLU networks for multiclass classification
Thijs Bos
Johannes Schmidt-Hieber
49
22
0
02 Aug 2021
Universal approximations of invariant maps by neural networks
Universal approximations of invariant maps by neural networks
Dmitry Yarotsky
60
210
0
26 Apr 2018
Deep Learning in Neural Networks: An Overview
Deep Learning in Neural Networks: An Overview
Jürgen Schmidhuber
HAI
167
16,311
0
30 Apr 2014
1