2 citations · 4 across the 6 of their papers we have counts for
5 papers · 1 filter
Does simple trump complex? Comparing strategies for adversarial robustness in DNNs
William Brooks, Marelie H. Davel, Coenraad Mouton
Deep Neural Networks (DNNs) have shown substantial success in various applications but remain vulnerable to adversarial attacks. This study aims to identify and isolate the compone…
KnowIt: Deep Time Series Modeling and Interpretation
M. W. Theunissen, R. Rabe, H. L. Potgieter +1
KnowIt (Knowledge discovery in time series data) is a flexible framework for building deep time series models and interpreting them. It is implemented as a Python toolkit, with sou…
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…
Is network fragmentation a useful complexity measure?
Coenraad Mouton, Randle Rabe, Daniël G. Haasbroek +3
It has been observed that the input space of deep neural network classifiers can exhibit `fragmentation', where the model function rapidly changes class as the input space is trave…