26 citations · 73 across the 10 of their papers we have counts for
4 papers · 1 filter
Unsupervised Domain Adaptation from Synthetic to Real Images for Anchorless Object Detection
Tobias Scheck, Ana Perez Grassi, Gangolf Hirtz
Synthetic images are one of the most promising solutions to avoid high costs associated with generating annotated datasets to train supervised convolutional neural networks (CNN).…
Where to drive: free space detection with one fisheye camera
Tobias Scheck, Adarsh Mallandur, Christian Wiede +1
The development in the field of autonomous driving goes hand in hand with ever new developments in the field of image processing and machine learning methods. In order to fully exp…
A CNN-based Feature Space for Semi-supervised Incremental Learning in Assisted Living Applications
Tobias Scheck, Ana Perez Grassi, Gangolf Hirtz
A Convolutional Neural Network (CNN) is sometimes confronted with objects of changing appearance ( new instances) that exceed its generalization capability. This requires the CNN t…
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning
Tobias Scheck, Roman Seidel, Gangolf Hirtz
Recent work about synthetic indoor datasets from perspective views has shown significant improvements of object detection results with Convolutional Neural Networks(CNNs). In this…