38 citations · 50 across the 21 of their papers we have counts for
3 papers · 1 filter
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities
Matthias Rottmann, Pascal Colling, Thomas-Paul Hack +4
We present a method that "meta" classifies whether seg-ments predicted by a semantic segmentation neural networkintersect with the ground truth. For this purpose, we employ measure…
Classification Uncertainty of Deep Neural Networks Based on Gradient Information
Philipp Oberdiek, Matthias Rottmann, Hanno Gottschalk
We study the quantification of uncertainty of Convolutional Neural Networks (CNNs) based on gradient metrics. Unlike the classical softmax entropy, such metrics gather information…
Deep Bayesian Active Semi-Supervised Learning
Matthias Rottmann, Karsten Kahl, Hanno Gottschalk
In many applications the process of generating label information is expensive and time consuming. We present a new method that combines active and semi-supervised deep learning to…