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ARAS Human Activity Datasets in Multiple Homes with Multiple Residents

Year: 2013

Type: conference-paper

Abstract: The real world human activity datasets are of great importance in development of novel machine learning methods for automatic recognition of human activities in smart environments. In this study, we present the details of ARAS (Activity Recogni- tion with Ambient Sensing) human activity recognit

Source: Proceedings of the ICTs for improving Patients Rehabilitation Research Techniques

DOI: 10.4108/icst.pervasivehealth.2013.252120

Authors: Hande Alemdar, Ozlem Durmaz Incel, Halil Ertan, Cem Ersoy

Institutions: Boğaziçi University, Galatasaray University

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: Galatasaray Üniversitesi