OSDaR23: Open Sensor Data for Rail 2023

arXiv:2305.03001v2 Announce Type: replace
Abstract: To achieve a driverless train operation on mainline railways, actual and potential obstacles for the train's driveway must be detected automatically by appropriate sensor systems. Machine learning algorithms have proven to be powerful tools for this task during the last years. However, these algorithms require large amounts of high-quality annotated data containing railway-specific objects as training data. Unfortunately, all of the publicly available datasets that tackle this requirement are restricted in some way. Therefore, this …

abstract algorithms arxiv cs.cv cs.ro data however machine machine learning machine learning algorithms obstacles rail sensor systems tools train type