Matches in SemOpenAlex for { <https://semopenalex.org/work/W2023921745> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W2023921745 abstract "In this work, we compare two generative models including Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) with Support Vector Machine (SVM) classifier for the recognition of six human daily activity (i.e., standing, walking, running, jumping, falling, sitting-down) from a single waist-worn tri-axial accelerometer signals through 4-fold cross-validation and testing on a total of thirteen subjects, achieving an average recognition accuracy of 96.43% and 98.21% in the first experiment and 95.51% and 98.72% in the second, respectively. The results demonstrate that both HMM and GMM are not only able to learn but also capable of generalization while the former outperformed the latter in the recognition of daily activities from a single waist worn tri-axial accelerometer. In addition, these two generative models enable the assessment of human activities based on acceleration signals with varying lengths." @default.
- W2023921745 created "2016-06-24" @default.
- W2023921745 creator A5003589267 @default.
- W2023921745 creator A5048330288 @default.
- W2023921745 creator A5051256188 @default.
- W2023921745 creator A5054380056 @default.
- W2023921745 creator A5062670921 @default.
- W2023921745 date "2012-06-01" @default.
- W2023921745 modified "2023-09-26" @default.
- W2023921745 title "Generative models for automatic recognition of human daily activities from a single triaxial accelerometer" @default.
- W2023921745 cites W1974344651 @default.
- W2023921745 cites W1993761347 @default.
- W2023921745 cites W1995126885 @default.
- W2023921745 cites W2032079330 @default.
- W2023921745 cites W2035454449 @default.
- W2023921745 cites W2046340070 @default.
- W2023921745 cites W2052690418 @default.
- W2023921745 cites W2068006147 @default.
- W2023921745 cites W2076552240 @default.
- W2023921745 cites W2103990602 @default.
- W2023921745 cites W2109192831 @default.
- W2023921745 cites W2125838338 @default.
- W2023921745 cites W2132691216 @default.
- W2023921745 cites W2168538666 @default.
- W2023921745 doi "https://doi.org/10.1109/ijcnn.2012.6252529" @default.
- W2023921745 hasPublicationYear "2012" @default.
- W2023921745 type Work @default.
- W2023921745 sameAs 2023921745 @default.
- W2023921745 citedByCount "10" @default.
- W2023921745 countsByYear W20239217452013 @default.
- W2023921745 countsByYear W20239217452014 @default.
- W2023921745 countsByYear W20239217452015 @default.
- W2023921745 countsByYear W20239217452018 @default.
- W2023921745 countsByYear W20239217452019 @default.
- W2023921745 countsByYear W20239217452020 @default.
- W2023921745 countsByYear W20239217452021 @default.
- W2023921745 crossrefType "proceedings-article" @default.
- W2023921745 hasAuthorship W2023921745A5003589267 @default.
- W2023921745 hasAuthorship W2023921745A5048330288 @default.
- W2023921745 hasAuthorship W2023921745A5051256188 @default.
- W2023921745 hasAuthorship W2023921745A5054380056 @default.
- W2023921745 hasAuthorship W2023921745A5062670921 @default.
- W2023921745 hasBestOaLocation W20239217452 @default.
- W2023921745 hasConcept C111919701 @default.
- W2023921745 hasConcept C117896860 @default.
- W2023921745 hasConcept C119857082 @default.
- W2023921745 hasConcept C121332964 @default.
- W2023921745 hasConcept C121687571 @default.
- W2023921745 hasConcept C12267149 @default.
- W2023921745 hasConcept C153180895 @default.
- W2023921745 hasConcept C154945302 @default.
- W2023921745 hasConcept C163716315 @default.
- W2023921745 hasConcept C167966045 @default.
- W2023921745 hasConcept C23224414 @default.
- W2023921745 hasConcept C28490314 @default.
- W2023921745 hasConcept C39890363 @default.
- W2023921745 hasConcept C41008148 @default.
- W2023921745 hasConcept C61224824 @default.
- W2023921745 hasConcept C62520636 @default.
- W2023921745 hasConcept C74650414 @default.
- W2023921745 hasConcept C89805583 @default.
- W2023921745 hasConcept C95623464 @default.
- W2023921745 hasConceptScore W2023921745C111919701 @default.
- W2023921745 hasConceptScore W2023921745C117896860 @default.
- W2023921745 hasConceptScore W2023921745C119857082 @default.
- W2023921745 hasConceptScore W2023921745C121332964 @default.
- W2023921745 hasConceptScore W2023921745C121687571 @default.
- W2023921745 hasConceptScore W2023921745C12267149 @default.
- W2023921745 hasConceptScore W2023921745C153180895 @default.
- W2023921745 hasConceptScore W2023921745C154945302 @default.
- W2023921745 hasConceptScore W2023921745C163716315 @default.
- W2023921745 hasConceptScore W2023921745C167966045 @default.
- W2023921745 hasConceptScore W2023921745C23224414 @default.
- W2023921745 hasConceptScore W2023921745C28490314 @default.
- W2023921745 hasConceptScore W2023921745C39890363 @default.
- W2023921745 hasConceptScore W2023921745C41008148 @default.
- W2023921745 hasConceptScore W2023921745C61224824 @default.
- W2023921745 hasConceptScore W2023921745C62520636 @default.
- W2023921745 hasConceptScore W2023921745C74650414 @default.
- W2023921745 hasConceptScore W2023921745C89805583 @default.
- W2023921745 hasConceptScore W2023921745C95623464 @default.
- W2023921745 hasLocation W20239217451 @default.
- W2023921745 hasLocation W20239217452 @default.
- W2023921745 hasOpenAccess W2023921745 @default.
- W2023921745 hasPrimaryLocation W20239217451 @default.
- W2023921745 hasRelatedWork W1503442776 @default.
- W2023921745 hasRelatedWork W2023921745 @default.
- W2023921745 hasRelatedWork W2041636156 @default.
- W2023921745 hasRelatedWork W2128232757 @default.
- W2023921745 hasRelatedWork W2160451891 @default.
- W2023921745 hasRelatedWork W2367316877 @default.
- W2023921745 hasRelatedWork W2378630083 @default.
- W2023921745 hasRelatedWork W2963736354 @default.
- W2023921745 hasRelatedWork W3124180900 @default.
- W2023921745 hasRelatedWork W4206197930 @default.
- W2023921745 isParatext "false" @default.
- W2023921745 isRetracted "false" @default.
- W2023921745 magId "2023921745" @default.
- W2023921745 workType "article" @default.