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Deep Learning Method for Cell-Wise Object Tracking, Velocity Estimation and Projection of Sensor Data over Time
These approaches derive scene dynamics implicitly by correlating novel input and memorized data utilizing ConvNets.
Quantification of Uncertainties in Deep Learning-based Environment Perception
In this work, we introduce a novel Deep Learning-based method to perceive the environment of a vehicle based on radar scans while accounting for uncertainties in its predictions.
Semantic Segmentation of Radar Detections using Convolutions on Point Clouds
State-of-the-art algorithms for environment perception based on radar scans build up on deep neural network architectures that can be costly in terms of memory and computation.
From prosumer to flexumer: Case study on the value of flexibility in decarbonizing the multi-energy system of a manufacturing company
However, to identify the necessary investments in energy conversion and storage technologies to leverage demand response (DR) potentials, companies need to assess the value of flexibility.
