Hybrid outlier detection (HOD) method in sensor data for human activity classification

[1]  Klemens Böhm,et al.  HiCS: High Contrast Subspaces for Density-Based Outlier Ranking , 2012, 2012 IEEE 28th International Conference on Data Engineering.

[2]  Lei Chen,et al.  A Weighted Moving Average-based Approach for Cleaning Sensor Data , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[3]  Tae-Seong Kim,et al.  A single tri-axial accelerometer-based real-time personal life log system capable of human activity recognition and exercise information generation , 2011, Personal and Ubiquitous Computing.

[4]  Miguel A. Labrador,et al.  A mobile platform for real-time human activity recognition , 2012, 2012 IEEE Consumer Communications and Networking Conference (CCNC).

[5]  Idit Keidar,et al.  Distributed data classification in sensor networks , 2010, PODC.

[6]  Alison Taubman Cybraphon: Collecting the Physical or the Digital at National Museums Scotland? , 2014, EVA.

[7]  Shikha Agrawal,et al.  Survey on Anomaly Detection using Data Mining Techniques , 2015, KES.

[8]  Wan-Yu Deng,et al.  Cross-person activity recognition using reduced kernel extreme learning machine , 2014, Neural Networks.

[9]  Ernestina Menasalvas Ruiz,et al.  MARS: A Personalised Mobile Activity Recognition System , 2012, 2012 IEEE 13th International Conference on Mobile Data Management.

[10]  Xiang Chen,et al.  A Framework for Daily Activity Monitoring and Fall Detection Based on Surface Electromyography and Accelerometer Signals , 2013, IEEE Journal of Biomedical and Health Informatics.

[11]  Ke Zhang,et al.  A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data , 2009, PAKDD.

[12]  Bo Sheng,et al.  Outlier detection in sensor networks , 2007, MobiHoc '07.

[13]  Faicel Chamroukhi,et al.  An Unsupervised Approach for Automatic Activity Recognition Based on Hidden Markov Model Regression , 2013, IEEE Transactions on Automation Science and Engineering.

[14]  Michael D. Lee,et al.  An Empirical Evaluation of Chernoff Faces, Star Glyphs, and Spatial Visualisations for Binary Data , 2003, InVis.au.

[15]  Jianzhong Li,et al.  Unsupervised Outlier Detection in Sensor Networks Using Aggregation Tree , 2007, ADMA.

[16]  Osman Hegazy,et al.  Outliers detection and classification in wireless sensor networks , 2013 .

[17]  Ran Wolff,et al.  Noname manuscript No. (will be inserted by the editor) In-Network Outlier Detection in Wireless Sensor Networks , 2022 .

[18]  Andrei Petrovski,et al.  ClusterNN: A Hybrid Classification Approach to Mobile Activity Recognition , 2015, MoMM.

[19]  Bernadette Dorizzi,et al.  Human activities of daily living recognition using fuzzy logic for elderly home monitoring , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[20]  A. Ben Hamza,et al.  Cluster pca for outliers detection in high-dimensional data , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[21]  Ying Liu,et al.  Cluster-based outlier detection , 2009, Ann. Oper. Res..

[22]  Hui Liu,et al.  Healthy: A Diary System Based on Activity Recognition Using Smartphone , 2013, 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems.

[23]  Tae-Seong Kim,et al.  A Triaxial Accelerometer-Based Physical-Activity Recognition via Augmented-Signal Features and a Hierarchical Recognizer , 2010, IEEE Transactions on Information Technology in Biomedicine.

[24]  Lei Gao,et al.  Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems. , 2014, Medical engineering & physics.

[25]  Vikramaditya Jakkula,et al.  Outlier Detection in Smart Environment Structured Power Datasets , 2010, 2010 Sixth International Conference on Intelligent Environments.

[26]  Hugo Martins,et al.  A machine learning technique in a multi-agent framework for online outliers detection in Wireless Sensor Networks , 2015, IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society.

[27]  Nirvana Meratnia,et al.  Outlier Detection Techniques for Wireless Sensor Networks: A Survey , 2008, IEEE Communications Surveys & Tutorials.

[28]  Tim Dallas,et al.  Feature Selection and Activity Recognition System Using a Single Triaxial Accelerometer , 2014, IEEE Transactions on Biomedical Engineering.

[29]  Héctor Pomares,et al.  Human activity recognition based on a sensor weighting hierarchical classifier , 2013, Soft Comput..

[30]  Tae-Seong Kim,et al.  Mobile Motion Sensor-Based Human Activity Recognition and Energy Expenditure Estimation in Building Environments , 2013 .

[31]  Trevor P. Martin,et al.  Fuzzy Ambient Intelligence for Next Generation Telecare , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[32]  Majid Sarrafzadeh,et al.  Designing a Robust Activity Recognition Framework for Health and Exergaming Using Wearable Sensors , 2014, IEEE Journal of Biomedical and Health Informatics.

[33]  Yi Liu,et al.  One-against-all multi-class SVM classification using reliability measures , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[34]  M. Palaniswami,et al.  Distributed Anomaly Detection in Wireless Sensor Networks , 2006, 2006 10th IEEE Singapore International Conference on Communication Systems.

[35]  Xuelong Li,et al.  Rank Preserving Discriminant Analysis for Human Behavior Recognition on Wireless Sensor Networks , 2014, IEEE Transactions on Industrial Informatics.

[36]  Cem Ersoy,et al.  Online Human Activity Recognition on Smart Phones , 2012 .

[37]  Dimitrios Gunopulos,et al.  Online outlier detection in sensor data using non-parametric models , 2006, VLDB.

[38]  Edward Sazonov,et al.  Highly Accurate Recognition of Human Postures and Activities Through Classification With Rejection , 2014, IEEE Journal of Biomedical and Health Informatics.