Improving Indoor occupancy estimation using a hybrid CNN-LSTM approach
Author:
Affiliation:
1. School of Engineering and Technology, Christ (Deemed to be) University,Department of Computer Science and Engineering,Bengaluru,India
2. Universiti Putra,Department of Computer Science,Serdany,Selangor,Malaysia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9862308/9862027/09862328.pdf?arnumber=9862328
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1. Occupancy modeling on non-intrusive indoor environmental data through machine learning;Building and Environment;2024-04
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