Classifying imbalanced multi-modal sensor data for human activity recognition in a smart home using deep learning

In smart homes, data generated from real-time sensors for human activity recognition is complex, noisy and imbalanced. It is a significant challenge to create machine learning models that can classify activities which are not as commonly occurring as other activities. Machine learning models designe...

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Bibliographic Details
Main Authors: Ali A Alani, Georgina Cosma, Aboozar Taherkhani
Format: Default Conference proceeding
Published: 2020
Subjects:
Deep Learning
multi-sensor data
multi-modal data
imbalanced data
Human Activity Recognition
Online Access:https://hdl.handle.net/2134/13061723.v1
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https://hdl.handle.net/2134/13061723.v1

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