Comparing Deep Learning and Human Crafted Features for Recognising Hand Activities of Daily Living from Wearables-Reference-Cited by-同舟云学术

Comparing Deep Learning and Human Crafted Features for Recognising Hand Activities of Daily Living from Wearables

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 23rd IEEE International Conference on Mobile Data Management (MDM)
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Author:

Diamantidou Eleni¹,Giakoumis Dimitrios¹,Votis Konstantinos¹,Tzovaras Dimitrios¹,Likothanassis Spiridon²

Affiliation:

1. Centre for Research and Technology Hellas, Information Technologies Institute,Thermi,Greece,57001

2. University of Patras,Computer Engineering and Informatics Department,Patra,Greece,26504

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9861039/9861093/09861108.pdf?arnumber=9861108

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4. Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers

5. Feature extraction using convolution neural networks (cnn) and deep learning;jogin;2018 3rd IEEE International Conference on Recent Trends in Electronics Information & Communication Technology (RTEICT),2018

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