30 citations · 44 across the 12 of their papers we have counts for
3 papers · 1 filter
Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training by Receptive Field Analysis
Mats L. Richter, Julius Schöning, Anna Wiedenroth +1
When optimizing convolutional neural networks (CNN) for a specific image-based task, specialists commonly overshoot the number of convolutional layers in their designs. By implicat…
Exploring the Properties and Evolution of Neural Network Eigenspaces during Training
Mats L. Richter, Leila Malihi, Anne-Kathrin Patricia Windler +1
In this work we explore the information processing inside neural networks using logistic regression probes \cite{probes} and the saturation metric \cite{featurespace_saturation}. W…
Size Matters
Mats L. Richter, Wolf Byttner, Ulf Krumnack +2
Fully convolutional neural networks can process input of arbitrary size by applying a combination of downsampling and pooling. However, we find that fully convolutional image class…