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7 papers · 1 filter
Impact of Batch Normalization on Convolutional Network Representations
Hermanus L. Potgieter, Coenraad Mouton, Marelie H. Davel
Batch normalization (BatchNorm) is a popular layer normalization technique used when training deep neural networks. It has been shown to enhance the training speed and accuracy of…
Neural Network-based Vehicular Channel Estimation Performance: Effect of Noise in the Training Set
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
Vehicular communication systems face significant challenges due to high mobility and rapidly changing environments, which affect the channel over which the signals travel. To addre…
The Missing Margin: How Sample Corruption Affects Distance to the Boundary in ANNs
Marthinus W. Theunissen, Coenraad Mouton, Marelie H. Davel
Classification margins are commonly used to estimate the generalization ability of machine learning models. We present an empirical study of these margins in artificial neural netw…
Exploring layerwise decision making in DNNs
Coenraad Mouton, Marelie H. Davel
While deep neural networks (DNNs) have become a standard architecture for many machine learning tasks, their internal decision-making process and general interpretability is still…
Stride and Translation Invariance in CNNs
Coenraad Mouton, Johannes C. Myburgh, Marelie H. Davel
Convolutional Neural Networks have become the standard for image classification tasks, however, these architectures are not invariant to translations of the input image. This lack…
Pre-interpolation loss behaviour in neural networks
Arthur E. W. Venter, Marthinus W. Theunissen, Marelie H. Davel
When training neural networks as classifiers, it is common to observe an increase in average test loss while still maintaining or improving the overall classification accuracy on t…