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A Closer Look at Reward Decomposition for High-Level Robotic Explanations
Explaining the behaviour of intelligent agents learned by reinforcement learning (RL) to humans is challenging yet crucial due to their incomprehensible proprioceptive states, variational intermediate goals, and resultant unpredictability.
Reinforcement Learning (RL)
Vocal Bursts Intensity Prediction
Neural Field Conditioning Strategies for 2D Semantic Segmentation
In this work, we explore the use of neural fields as decoders for 2D semantic segmentation.
Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels
To overcome the time-consuming data annotation, we generate a large number of ground-truth labels using a robotic setup.
Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation
Optical coherence tomography (OCT) is an imaging modality which is used in interventions due to its high spatial resolution of few micrometers and its temporal resolution of potentially several hundred volumes per second.
Towards Head Motion Compensation Using Multi-Scale Convolutional Neural Networks
Head pose estimation and tracking is useful in variety of medical applications.
