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Energy-Efficient and Interpretable Multisensor Human Activity Recognition via Deep Fused Lasso Net
Yu ZHOU
, Jingtao XIE
, Xiao ZHANG
, Wenhui WU
,
Sam KWONG
Department of Computing and Decision Sciences
Research output
:
Journal Publications
›
Journal Article (refereed)
›
peer-review
40
Citations (Scopus)
Overview
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Dive into the research topics of 'Energy-Efficient and Interpretable Multisensor Human Activity Recognition via Deep Fused Lasso Net'. Together they form a unique fingerprint.
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Computer Science
Human Activity Recognition
100%
multi sensor
20%
Physical Channel
20%
Physical Meaning
20%
Processing Cost
20%
Engineering
Acquired Data
33%
End Structure
33%
Physical Channel
33%
Processing Cost
33%
Recognition Model
33%