FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4207056144> ?p ?o ?g. }

• W4207056144 endingPage "160645" @default.
• W4207056144 startingPage "160635" @default.
• W4207056144 abstract "Activity recognition is an essential factor in the determination of daily routine of a human being. There exist numerous Human Activity Recognition (HAR) systems; however, an HAR with a practical accuracy is still in search and a challenge at large. The classifiers utilized in existing systems offer degrading recognition rates in various key environments such as depth camera environment among others. To address the limitation of degrading recognition rates, in this paper, we propose Maximum Entropy Markov Model (MEMM) that solves the degrading recognition rate problem. In MEMM, we model the states of activity recognition as the states of the model itself i.e. as the states of MEMM, and hence consider the observations of video-sensor as the observations of MEMM. Further, we use a modified version of Viterbi, a machine learning algorithm, to generate the most likely probable state sequence based on these observations. Then, from such a state sequence, we use MEMM to predict the activity state. We evaluate the performance MEMM against depth dataset having eleven different types of activities in a large-scale experimentation process. The results show that MEMM outperforms existing well-known methods by achieving a weighted average recognition rate 96.3% across the naturalistic dataset collected using depth camera." @default.
• W4207056144 created "2022-01-26" @default.
• W4207056144 creator A5004783243 @default.
• W4207056144 creator A5032105945 @default.
• W4207056144 creator A5037428435 @default.
• W4207056144 creator A5041711498 @default.
• W4207056144 creator A5065276883 @default.
• W4207056144 date "2021-01-01" @default.
• W4207056144 modified "2023-10-01" @default.
• W4207056144 title "Maximum Entropy Markov Model for Human Activity Recognition Using Depth Camera" @default.
• W4207056144 cites W129757148 @default.
• W4207056144 cites W1962571432 @default.
• W4207056144 cites W1995937139 @default.
• W4207056144 cites W2031540617 @default.
• W4207056144 cites W2034899024 @default.
• W4207056144 cites W2043084384 @default.
• W4207056144 cites W2070006916 @default.
• W4207056144 cites W2082009375 @default.
• W4207056144 cites W2085731903 @default.
• W4207056144 cites W2094815827 @default.
• W4207056144 cites W2107012990 @default.
• W4207056144 cites W2114665058 @default.
• W4207056144 cites W2136132422 @default.
• W4207056144 cites W2160000992 @default.
• W4207056144 cites W2161969291 @default.
• W4207056144 cites W2224722700 @default.
• W4207056144 cites W2246021102 @default.
• W4207056144 cites W2506886870 @default.
• W4207056144 cites W2518674461 @default.
• W4207056144 cites W2519616506 @default.
• W4207056144 cites W2529005704 @default.
• W4207056144 cites W2566887294 @default.
• W4207056144 cites W2748923651 @default.
• W4207056144 cites W2777182804 @default.
• W4207056144 cites W2780602937 @default.
• W4207056144 cites W2783170722 @default.
• W4207056144 cites W2883594635 @default.
• W4207056144 cites W2895520659 @default.
• W4207056144 cites W2966603308 @default.
• W4207056144 cites W2966888218 @default.
• W4207056144 cites W2969328148 @default.
• W4207056144 cites W2974089216 @default.
• W4207056144 cites W2996834291 @default.
• W4207056144 cites W3008119735 @default.
• W4207056144 cites W3008239847 @default.
• W4207056144 cites W3011934803 @default.
• W4207056144 cites W3016309391 @default.
• W4207056144 cites W3016552312 @default.
• W4207056144 cites W3082048539 @default.
• W4207056144 cites W3082167482 @default.
• W4207056144 cites W3094563209 @default.
• W4207056144 cites W4242041854 @default.
• W4207056144 doi "https://doi.org/10.1109/access.2021.3132559" @default.
• W4207056144 hasPublicationYear "2021" @default.
• W4207056144 type Work @default.
• W4207056144 citedByCount "10" @default.
• W4207056144 countsByYear W42070561442022 @default.
• W4207056144 countsByYear W42070561442023 @default.
• W4207056144 crossrefType "journal-article" @default.
• W4207056144 hasAuthorship W4207056144A5004783243 @default.
• W4207056144 hasAuthorship W4207056144A5032105945 @default.
• W4207056144 hasAuthorship W4207056144A5037428435 @default.
• W4207056144 hasAuthorship W4207056144A5041711498 @default.
• W4207056144 hasAuthorship W4207056144A5065276883 @default.
• W4207056144 hasBestOaLocation W42070561441 @default.
• W4207056144 hasConcept C105795698 @default.
• W4207056144 hasConcept C106301342 @default.
• W4207056144 hasConcept C119857082 @default.
• W4207056144 hasConcept C121332964 @default.
• W4207056144 hasConcept C121687571 @default.
• W4207056144 hasConcept C153180895 @default.
• W4207056144 hasConcept C154945302 @default.
• W4207056144 hasConcept C159886148 @default.
• W4207056144 hasConcept C163836022 @default.
• W4207056144 hasConcept C196956702 @default.
• W4207056144 hasConcept C23224414 @default.
• W4207056144 hasConcept C33923547 @default.
• W4207056144 hasConcept C41008148 @default.
• W4207056144 hasConcept C54907487 @default.
• W4207056144 hasConcept C60582962 @default.
• W4207056144 hasConcept C62520636 @default.
• W4207056144 hasConcept C98763669 @default.
• W4207056144 hasConceptScore W4207056144C105795698 @default.
• W4207056144 hasConceptScore W4207056144C106301342 @default.
• W4207056144 hasConceptScore W4207056144C119857082 @default.
• W4207056144 hasConceptScore W4207056144C121332964 @default.
• W4207056144 hasConceptScore W4207056144C121687571 @default.
• W4207056144 hasConceptScore W4207056144C153180895 @default.
• W4207056144 hasConceptScore W4207056144C154945302 @default.
• W4207056144 hasConceptScore W4207056144C159886148 @default.
• W4207056144 hasConceptScore W4207056144C163836022 @default.
• W4207056144 hasConceptScore W4207056144C196956702 @default.
• W4207056144 hasConceptScore W4207056144C23224414 @default.
• W4207056144 hasConceptScore W4207056144C33923547 @default.
• W4207056144 hasConceptScore W4207056144C41008148 @default.
• W4207056144 hasConceptScore W4207056144C54907487 @default.
• W4207056144 hasConceptScore W4207056144C60582962 @default.
• W4207056144 hasConceptScore W4207056144C62520636 @default.

• next