Cluster Centers Provide Good First Labels for Object Detection

Learning object detection models with a few labels, is possible due to ingenious few-shot techniques, and due to clever selection of images to be labeled. Few-shot techniques work with as few as 1 to 10 randomized labels per object class. We are curious if performance of randomized label selection can be improved by selecting 1 to 10 labels per...

Towards personalised automated driving: Prediction of preferred ACC behaviour based on manual driving

More and more Advanced Driver Assistance Systems (ADASs) are entering the market for improving both safety and comfort. Adaptive Cruise Control (ACC) is an ADAS application that has high interaction with the driver. ACC systems use limited sensor input and have only few configuration possibilities. This may result in the behaviour of the ACC not...

Large scale track analysis for wide area motion imagery surveillance

Wide Area Motion Imagery (WAMI) enables image based surveillance of areas that can cover multiple square kilometers. Interpreting and analyzing information from such sources, becomes increasingly time consuming as more data is added from newly developed methods for information extraction. Captured from a moving Unmanned Aerial Vehicle (UAV), the...

Applying machine learning techniques for forecasting flexibility of virtual power plants

Classification for Safety-Critical Car-Cyclist Scenarios Using Machine Learning

The number of fatal car-cyclist accidents is increasing. Advanced Driver Assistance Systems (ADAS) can improve the safety of cyclists, but they need to be tested with realistic safety-critical car-cyclist scenarios. In order to store only relevant scenarios, an online classification algorithm is needed. We demonstrate that machine learning...