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      Development of a Holistic System for Activity Classification Based on Multimodal Sensor Data

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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Wearable Sensors, Human Activity Recognition, Machine Learning, Ubiquitous Computing

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            Author and article information

            Contributors
            Conference
            July 2018
            July 2018
            : 1-4
            Affiliations
            Hochschule Mittweida

            Technikumplatz 17

            D-09648 Mittweida
            Article
            10.14236/ewic/HCI2018.167
            31a393fc-e043-49f5-b60c-f2557e783753
            © Rolletschke et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            HCI
            32
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            Product
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            REFERENCES

            1. Apple 2018 ARKit - Apple Developer May 03 2018 http://developer.apple.com/arkit/

            2. Apple 2018 Machine Learning - Apple Developer May 01 2018 http://developer.apple.com/machine-learning/

            3. 2017 Performance Analysis of Smartphone-Sensor Behavior for Human Activity Recognition IEEE Access 5 3095 3110

            4. 2017 IOD-CNN: Integrating Object Detection Networks for Event Recognition arXiv.org

            5. 2011 Accurate Activity Recognition Using a Mobile Phone Regardless of Device Orientation and Location Bsn 41 46

            6. 2017 DFKI and Hitachi jointly develop AI technology for human activity recognition of workers using wearable devices - News Releases June 4 2018 http://www.hitachi.com/New/cnews/month/2017/03/170308.html

            7. 2017 Robust human activity recognition from depth video using spatiotemporal multi-fused features Pattern Recognition 61 295 308

            8. 2018 Convolutional Neural Networks and Long Short-Term Memory for skeleton-based human activity and hand gesture recognition Pattern Recognition 76 80 94

            9. 2016 Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition Sensors 16 1 115

            10. 2018 turicreate - Turi Create simplifies the development of custom machine learning models May 06 2018 github.com/apple/turicreate

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