activity
20202022
most citedStride and Translation Invariance in CNNs

27 citations · 33 across the 6 of their papers we have counts for

collaborators

7 papers

cs.SD20222 cited

Efficient acoustic feature transformation in mismatched environments using a Guided-GAN

Walter Heymans, Marelie H. Davel, Charl van Heerden

We propose a new framework to improve automatic speech recognition (ASR) systems in resource-scarce environments using a generative adversarial network (GAN) operating on acoustic…

cs.SD20221 cited

Multi-style Training for South African Call Centre Audio

Walter Heymans, Marelie H. Davel, Charl van Heerden

Mismatched data is a challenging problem for automatic speech recognition (ASR) systems. One of the most common techniques used to address mismatched data is multi-style training (…

cs.LG20221 cited

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…

cs.LG2021

Tracking translation invariance in CNNs

Johannes C. Myburgh, Coenraad Mouton, Marelie H. Davel

Although Convolutional Neural Networks (CNNs) are widely used, their translation invariance (ability to deal with translated inputs) is still subject to some controversy. We explor…

cs.LG202127 cited

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…

cs.LG20212 cited

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…