The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Daily Activity Feature Selection in Smart Homes Based on Pearson Correlation Coefficient
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Citations
Cites
Activity Recognition from User-Annotated Acceleration Data
Bao, L., & Intille, S. S. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24646-6_1 · Cited by 3,147
A review of smart homes—Present state and future challenges
Chan, M., Estève, D., Escriba, C., & Campo, E. (2008) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2008.02.001 · Cited by 1,007
A Knowledge-Driven Approach to Activity Recognition in Smart Homes
Chen, L., Nugent, C. D., & Wang, H. (2012) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2011.51 · Cited by 589
An Improved Ant Colony Optimization Algorithm Based on Hybrid Strategies for Scheduling Problem
Deng, W., Xu, J., & Zhao, H. (2019) · IEEE Access · doi:10.1109/access.2019.2897580 · Cited by 560
Ensembles of Deep LSTM Learners for Activity Recognition using Wearables
Guan, Y., & Plötz, T. (2017) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3090076 · Cited by 511
Activity recognition on streaming sensor data
Krishnan, N. C., & Cook, D. J. (2014) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2012.07.003 · Cited by 488
Tapia, E. M., Intille, S. S., Haskell, W., Larson, K., Wright, J., King, A., & Friedman, R. (2007) · 2007 11th IEEE International Symposium on Wearable Computers · doi:10.1109/iswc.2007.4373774 · Cited by 458
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
Patterson, D. J., Fox, D., Kautz, H., & Philipose, M. (2005) · Ninth IEEE International Symposium on Wearable Computers (ISWC'05) · doi:10.1109/iswc.2005.22 · Cited by 452
A novel collaborative optimization algorithm in solving complex optimization problems
Deng, W., Zhao, H., Zou, L., et al. (2016) · Soft Computing · doi:10.1007/s00500-016-2071-8 · Cited by 384
Study on an improved adaptive PSO algorithm for solving multi-objective gate assignment
Deng, W., Zhao, H., Yang, X., Xiong, J., Sun, M., & Li, B. (2017) · Applied Soft Computing · doi:10.1016/j.asoc.2017.06.004 · Cited by 364
Cited by
An Improved Quantum-Inspired Differential Evolution Algorithm for Deep Belief Network
Deng, W., Liu, H., Xu, J., Zhao, H., & Song, Y. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.2983233 · Cited by 429
Pang, Y.-N., Liu, B., Liu, J., Wan, S. P., Wu, T., He, X., Yuan, J., Zhou, X., Long, K., & Wu, Q. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3032646 · Cited by 67
Metadata
- Authors
- Liu, Y., Mu, Y., Chen, K., Li, Y., & Guo, J.
- Venue
- Neural Processing Letters
- Published
- 2020-01-07
- Volume
- 51
- Issue
- 2
- Pages
- 1771-1787
- ISSN
- 1370-4621 (ISSN-L)
- 1573-773X
- OpenAlex
- W2999681686
- Cited by
- 283
- References
- 39
- FWCI
- 13.82
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, Y., Mu, Y., Chen, K., Li, Y., & Guo, J. (2020). Daily Activity Feature Selection in Smart Homes Based on Pearson Correlation Coefficient. Neural Processing Letters. https://doi.org/10.1007/s11063-019-10185-8
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
