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Human Data Understanding
Sensors, Models, Knowledge
ISSN: 2701-9446
Herausgeber:
Prof. Dr.-Ing. Frank Deinzer (Technische Hochschule Würzburg-Schweinfurt)
Prof. Dr.-Ing. Marcin Grzegorzek (Universität zu Lübeck)
Technical innovation results in an enormous amount of data and information that can be used for the description and analysis of individual humans and whole populations. In this context, methods combining different sensor modalities using suitable models are investigated to advance the understanding of the human physical and mental state. This book series is dedicated to this broad field of research.
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Bislang erschienene Bände:
| Bd. 1: Frank Ebner Smartphone-Based 3D Indoor Localization and Navigation |
| Bd. 2: Frédéric Li Deep Learning for Time-series Classification Enhanced by Transfer Learning Based on Sensor Modality Discrimination |
| Bd. 3: Muhammad Adeel Nisar Sensor-Based Human Activity Recognition for Assistive Health Technologies |
| Bd. 4: Xinyu Huang Sensor-based Sleep Stage Classification Using Deep Learning |
| Bd. 5: Raoul Hoffmann Analysing Data from Capacitive Floor Sensors for Human Gait Assessment Using Artificial Neural Networks |
| Bd. 6: Philip Johannes Gouverneur Machine Learning Methods for Pain Investigation Using Physiological Signals |
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