Accidents often occur in the petrochemical industry, which have a negative impact on society
and the environment. Learning Process Safety Knowledge (PSK) from accident cases is …

This work proposes an active learning (AL) methodology to create models for the
segmentation of fire and smoke in video images. With this model, a model learns in an …

Informed machine learning describes the injection of prior knowledge into learning systems.
It can help to improve generalization, especially when training data is scarce. However, the …

Driving on roads is restricted by various traffic rules, aiming to ensure safety for all traffic
participants. However, human road users usually do not adhere to these rules strictly …

Deep learning has revolutionized autonomous driving by enabling vehicles to perceive and
interpret their surroundings with remarkable accuracy. This progress is attributed to various …

Reinforcement Learning is a highly active research field with promising advancements. In
the field of autonomous driving, however, often very simple scenarios are being examined …

Informed learning approaches explicitly integrate prior knowledge into learning systems,
which can reduce data needs and increase robustness. However, existing work typically …

Artificial Intelligence (AI) techniques through Learning-Enabled Components (LEC) are
widely employed in Automated Driving Systems (ADS) to support operation perception and …

Prior parameter distributions provide an elegant way to represent prior expert and world
knowledge for informed learning. Previous work has shown that using such informative …

Artificial Intelligence (AI) is deemed the key technology for the development of auto nomous
driving functions. To ensure safety they must be comprehensively trained, validated and …