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Invariant Integration in Deep Convolutional Feature Space

Invariant Integration in Deep Convolutional Feature Space

The European Symposium on Artificial Neural Networks (ESANN), 2020
20 April 2020
M. Rath
Alexandru Paul Condurache
    MDE
ArXiv (abs)PDFHTML

Papers citing "Invariant Integration in Deep Convolutional Feature Space"

6 / 6 papers shown
LaneCPP: Continuous 3D Lane Detection using Physical Priors
LaneCPP: Continuous 3D Lane Detection using Physical Priors
M. Pittner
J. Janai
Alexandru Paul Condurache
260
32
0
12 Jun 2024
Deep Neural Networks with Efficient Guaranteed Invariances
Deep Neural Networks with Efficient Guaranteed InvariancesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
M. Rath
Alexandru Paul Condurache
304
5
0
02 Mar 2023
Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep
  Neural Network, a Survey
Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep Neural Network, a SurveyArtificial Intelligence Review (Artif Intell Rev), 2022
Paul Wimmer
Jens Mehnert
Alexandru Paul Condurache
DD
372
35
0
17 May 2022
Interspace Pruning: Using Adaptive Filter Representations to Improve
  Training of Sparse CNNs
Interspace Pruning: Using Adaptive Filter Representations to Improve Training of Sparse CNNsComputer Vision and Pattern Recognition (CVPR), 2022
Paul Wimmer
Jens Mehnert
Alexandru Paul Condurache
CVBM
173
31
0
15 Mar 2022
Improving the Sample-Complexity of Deep Classification Networks with
  Invariant Integration
Improving the Sample-Complexity of Deep Classification Networks with Invariant IntegrationVISIGRAPP (VISIGRAPP), 2022
M. Rath
Alexandru Paul Condurache
169
8
0
08 Feb 2022
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey
M. Rath
Alexandru Paul Condurache
ViTAI4CE
420
15
0
30 Jun 2020
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