Improving data classification accuracy in sensor networks using hybrid outlier detection in HAR
Author:
Affiliation:
1. University College of Engineering Panruti, Panruti, Tamilnadu, India
2. University College of Engineering Tindivanam, Tindivanam, Tamilnadu, India
Publisher
IOS Press
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Reference51 articles.
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3. A.S. Evani , B. Sreenivasan , J.S. Sudesh , M. Prakash and J. Bapat , Activity recognition using wearable sensors for healthcare, in the proceedings of Sensor Technologies and Applications (SENSORCOMM) (2013), 173–177.
4. Alsheikh et al., Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications, IEEE Communications - Surveys & Tutorials (2014), 1996–2018.
5. Designing a robust activity recognition framework for health and exergaming using wearable sensors;Alshurafa;Journal of Biomedical and Health Informatics,2014
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Using Multivariate Outliers from Smartphone Sensor Data to Detect Physical Barriers While Walking in Urban Areas;Technologies;2020-10-26
2. Evaluating the Impact of a Two-Stage Multivariate Data Cleansing Approach to Improve to the Performance of Machine Learning Classifiers: A Case Study in Human Activity Recognition;Sensors;2020-03-27
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