CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12941 > Article
Paper
7 December 2023 An improved BiLSTM model for daily activity recognition
Xingchen Li, Yang Feng, Dingyi Li, Yaqing Liu
Author Affiliations +
Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129412O (2023) https://doi.org/10.1117/12.3011584
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
Approaches and models of intelligent control have been developed to improve quality of daily life. Smart home solution has been designed to provide convenience for residents by recognizing their daily activities. In order to improve the performance of daily activity recognition, here we proposed an improved BiLSTM-Attention based daily activity recognition method which introduced dimension upgrading. Firstly, we used the feature extraction algorithm to obtain the relevant feature vectors. Secondly the feature vectors were transferred to the Bi-directional Long Short-Term Memory (BiLSTM) model for learning the time-series relationship between features and daily activity recognition. Thirdly, the BiLSTM model and attention mechanism were combined to improve the discrimination capability of daily activity features. Finally, the input data of the BiLSTM-Attention model was upgraded to improve the performance of daily activity recognition. The the F1-score of BiLSTM-Attention model was improved over the benchmark method by 5% using the public dataset CASAS_Cairo, and by 19% after the data dimension upgrading. On the public dataset CASAS_Aruba, the F1-score was improved 6% by using BiLSTM-Attention model and improved 11% by using additionally data dimension upgrading.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Xingchen Li, Yang Feng, Dingyi Li, and Yaqing Liu "An improved BiLSTM model for daily activity recognition", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129412O (7 December 2023); https://doi.org/10.1117/12.3011584
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 7 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling
Sensors
Feature extraction
Machine learning
Neural networks
Deep learning
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top