4 citations · 8 across the 4 of their papers we have counts for
6 papers
Evaluation of deep lift pose models for 3D rodent pose estimation based on geometrically triangulated data
Indrani Sarkar, Indranil Maji, Charitha Omprakash +3
The assessment of laboratory animal behavior is of central interest in modern neuroscience research. Behavior is typically studied in terms of pose changes, which are ideally captu…
Uncertainty-Aware Temporal Self-Learning (UATS): Semi-Supervised Learning for Segmentation of Prostate Zones and Beyond
Anneke Meyer, Suhita Ghosh, Daniel Schindele +4
Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision into transition zone (TZ) and pe…
Gradient-Adjusted Neuron Activation Profiles for Comprehensive Introspection of Convolutional Speech Recognition Models
Andreas Krug, Sebastian Stober
Deep Learning based Automatic Speech Recognition (ASR) models are very successful, but hard to interpret. To gain better understanding of how Artificial Neural Networks (ANNs) acco…
Visualizing Deep Neural Networks for Speech Recognition with Learned Topographic Filter Maps
Andreas Krug, Sebastian Stober
The uninformative ordering of artificial neurons in Deep Neural Networks complicates visualizing activations in deeper layers. This is one reason why the internal structure of such…
Hybrid Active Inference
André Ofner, Sebastian Stober
We describe a framework of hybrid cognition by formulating a hybrid cognitive agent that performs hierarchical active inference across a human and a machine part. We suggest that,…
Transfer Learning for Speech Recognition on a Budget
Julius Kunze, Louis Kirsch, Ilia Kurenkov +3
End-to-end training of automated speech recognition (ASR) systems requires massive data and compute resources. We explore transfer learning based on model adaptation as an approach…