In many application domains data from different sources are increasingly available to
thoroughly monitor and describe a system or device. Especially within the industrial …

Long-term hurricane predictions have been of acute interest in order to protect the
community from the loss of lives, and environmental damage. Such predictions help by …

Responsive forestry management is critical to carbon management and climate change
mitigation. The United Nation's Intergovernmental Panel on Climate Change (IPCC) Special …

Robot assembly tasks can fail due to unpredictable errors and can only continue with the
manual intervention of a human operator. Recently, we proposed an exception strategy …

We propose a deep structure encoder using Volterra Neural Networks (VNNs) to seek a
latent representation of multi-modal data whose features are jointly captured by a union of …

Abstract Machine Learning and especially deep neural networks are more and more used in
industrial applications, because they offer new possibilities to gain knowledge from the …

Machine learning implementations in an industrial setting poses various challenges due to
the heterogeneous nature of the data sources. A classical machine learning algorithm …

In this work, we demonstrate the ability to exploit sensing modalities for mitigating an
unrepresented modality or for potentially re-targeting resources. This is tantamount to …

Human history is filled with inventions and other innovations that resulted in a significant and
lasting change in our civilization's course of development. From gasoline-powered vehicles …

Single sensor, such as 3D LiDAR camera, has relatively limited perception performance of
providing comprehensive environmental information though the perception results from …