Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine
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- 1 January 2012
- book chapter
- conference paper
- Published by Springer Science and Business Media LLC in Lecture Notes in Computer Science
Abstract
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This publication has 12 references indexed in Scilit:
- Pervasive computing at scale: Transforming the state of the artPervasive and Mobile Computing, 2012
- Activity recognition using cell phone accelerometersACM SIGKDD Explorations Newsletter, 2011
- Machine Learning Methods for Classifying Human Physical Activity from On-Body AccelerometersSensors, 2010
- Activity-Based ComputingIEEE Pervasive Computing, 2008
- A Hardware-friendly Support Vector Machine for Embedded Automotive Applications2007 International Joint Conference on Neural Networks, 2007
- Classification of a known sequence of motions and postures from accelerometry data using adapted Gaussian mixture modelsPhysiological Measurement, 2006
- Applications of Support Vector Machines to Speech RecognitionIEEE Transactions on Signal Processing, 2004
- Improvements to Platt's SMO Algorithm for SVM Classifier DesignNeural Computation, 2001
- Mixing floating- and fixed-point formats for neural network learning on neuroprocessorsMicroprocessing and Microprogramming, 1996
- The Nature of Statistical Learning TheoryPublished by Springer Science and Business Media LLC ,1995