TUdatalib : Rate of convergence of image classifiers based on convolutional neural networks: Implementations of the estimates and links to image data sets

Browse by

Titles Authors Type By Submit Date Subjects DFG subject classifications

This collection contains the most important parts to be able to reproduce the simulation parts of the image data used in the research project "Rate of convergence of image classifiers based on convolutional neural networks" funded by the German Research Foundation (DFG project number: 449102119, see https://gepris.dfg.de/gepris/projekt/449102119). In addition, the collection contains references to the image datasets that were used. The collection is structured into the three papers of the project, which include simulation parts.

Recent Submissions

Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling: Implementations of the estimates and links to image data sets

Walter, Benjamin (2023-05-27)
Analysis of convolutional neural network image classifiers in a rotationally symmetric model: Implementations of the estimates and links to image data sets

Kohler, Michael; Walter, Benjamin (2023-05-27)
On the rate of convergence of image classifiers based on convolutional neural networks: Implementations of the estimates and links to image data sets

Kohler, Michael; Krzyżak, Adam; Walter, Benjamin (2023-05-24)

Rate of convergence of image classifiers based on convolutional neural networks: Implementations of the estimates and links to image data sets

Browse by

Recent Submissions

Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling: Implementations of the estimates and links to image data sets ﻿

Analysis of convolutional neural network image classifiers in a rotationally symmetric model: Implementations of the estimates and links to image data sets ﻿

On the rate of convergence of image classifiers based on convolutional neural networks: Implementations of the estimates and links to image data sets ﻿

Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling: Implementations of the estimates and links to image data sets

Analysis of convolutional neural network image classifiers in a rotationally symmetric model: Implementations of the estimates and links to image data sets

On the rate of convergence of image classifiers based on convolutional neural networks: Implementations of the estimates and links to image data sets