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Recognizing and classifying a golf swing using accelerometer in a Smartwatch
Krüger, Anders
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
2017 (English)
Independent thesis Advanced level (professional degree), 20 credits / 30 HE credits
Student thesis
Place, publisher, year, edition, pages
2017. , p. 34
Keywords [en]
pattern recognition, machine learning, 3-axis accelerometer, golf swing
National Category
Interaction Technologies
Identifiers
URN:
urn:nbn:se:bth-14685
OAI: oai:DiVA.org:bth-14685
DiVA, id:
diva2:1114198
External cooperation
Wireless independent provider
Subject / course
Degree Project in Master of Science in Engineering 30.0
Educational program
PAACI Master of Science in Game and Software Engineering
Supervisors
Aspvall, Bengt, Professor
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Examiners
Goswami, Prashant, Universitetslektor
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
Available from:
2017-06-26
Created:
2017-06-22
Last updated:
2022-05-12
Bibliographically approved
Open Access in DiVA
fulltext
(1280 kB)
2100 downloads
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FULLTEXT01.pdf
File size
1280 kB
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SHA-512
73d2576ec2ba682e2a4d36bb6678e820f2743eee353506e0ddb80571b1e821883663a4ff92bb15059da5dfbf129a764631794636ac887ba67f2ec5877e3ab510
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fulltext
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application/pdf
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Department of Software Engineering
On the subject
Interaction Technologies
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Total: 2100 downloads
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Direct link
http://bth.diva-portal.org/smash/record.jsf?pid=diva2:1114198
Cite
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apa
ieee
modern-language-association-8th-edition
vancouver
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apa
ieee
modern-language-association-8th-edition
vancouver
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de-DE
en-GB
en-US
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nn-NB
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