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Found 12 papers, 0 papers with code
An Open-Source Modular Robotic System for Telepresence and Remote Disinfection
This work presents a modular mobile robot for telepresence and disinfection with UVC lamps.
Robotics
Reinforcement Learning Approaches in Social Robotics
The scope of the paper is focused particularly on studies that include social physical robots and real-world human-robot interactions with users.
Online Guest Detection in a Smart Home using Pervasive Sensors and Probabilistic Reasoning
This paper aims at addressing this challenge and presents a probabilistic approach able to estimate the number of persons in the environment at each time step.
Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring
To validate our approach we demonstrate, on the one hand, the ability of our system to perform probabilistic reasoning over multi-modal probability distributions, and on the other hand, the learning of probabilistic logical rules from anchored objects produced by perceptual observations.
Learning Generative Image Object Manipulations from Language Instructions
The use of adequate feature representations is essential for achieving high performance in high-level human cognitive tasks in computational modeling.
Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations
Therefore, we further propose Bayesian learning to resolve such inconsistencies between the natural language grounding and a robot's world representation by exploiting spatio-relational information that is implicitly present in instructions given by a human.
Semantic Referee: A Neural-Symbolic Framework for Enhancing Geospatial Semantic Segmentation
Understanding why machine learning algorithms may fail is usually the task of the human expert that uses domain knowledge and contextual information to discover systematic shortcomings in either the data or the algorithm.
Interactive user interface based on Convolutional Auto-encoders for annotating CT-scans
It was discovered that the experienced usability and how the users interactied with the system differed between the users.
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification
Automatic sleep staging is a challenging problem and state-of-the-art algorithms have not yet reached satisfactory performance to be used instead of manual scoring by a sleep technician.
Automatic Sleep Stage Classification
Dimensionality Reduction
+2
Reasoning for Improved Sensor Data Interpretation in a Smart Home
The ontology of this paradigm is inspired form the SSN ontology (Semantic Sensor Network) and used for representation of both the sensor data and the contextual information.
