{"data":{"id":"10.6084/m9.figshare.4508744.v1","type":"dois","attributes":{"doi":"10.6084/m9.figshare.4508744.v1","prefix":"10.6084","suffix":"m9.figshare.4508744.v1","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"LUIS MIRALLES","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Comparative Analysis of Artificial Hydrocarbon Networks an Data-Driven Approaches for Human Activity Recognition"}],"publisher":"figshare","container":{},"publicationYear":2016,"subjects":[{"subject":"Computer Engineering"},{"subject":"80602 Computer-Human Interaction","subjectScheme":"FOR"},{"subject":"FOS: Psychology","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Psychology","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Applied Computer Science"},{"subject":"Computer Software"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"80109 Pattern Recognition and Data Mining","subjectScheme":"FOR"},{"subject":"170203 Knowledge Representation and Machine Learning","subjectScheme":"FOR"}],"contributors":[],"dates":[{"date":"2016-12-31","dateType":"Created"},{"date":"2016-12-31","dateType":"Updated"},{"date":"2016","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsIdenticalTo","relatedIdentifier":"10.6084/m9.figshare.4508744","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["0 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"In recent years computing and sensing technologies advances contribute to develop effective human activity recognition systems. In context-aware and ambient assistive living applications, classification of body postures and movements, aids in the development of health systems that improve the quality of life of the disabled and the elderly. In this paper we describe a comparative analysis of data-driven activity recognition techniques against a novel supervised learning technique called artificial hydrocarbon networks (AHN). We prove that artificial hydrocarbon networks are suitable for efficient body postures and movements classification, providing a comparison between its performance and other well-known supervised learning methods.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://figshare.com/articles/dataset/Comparative_Analysis_of_Artificial_Hydrocarbon_Networks_an_Data-Driven_Approaches_for_Human_Activity_Recognition/4508744/1","contentUrl":null,"metadataVersion":4,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":1,"viewsOverTime":[{"yearMonth":"2025-04","total":1}],"downloadCount":0,"downloadsOverTime":[{"yearMonth":"2025-04","total":0}],"referenceCount":0,"citationCount":0,"citationsOverTime":[],"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2016-12-31T18:32:01.000Z","registered":"2016-12-31T18:32:02.000Z","published":"2016","updated":"2025-05-01T08:11:32.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.4508744.v1","type":"media"}},"references":{"data":[]},"citations":{"data":[]},"parts":{"data":[]},"partOf":{"data":[]},"versions":{"data":[]},"versionOf":{"data":[]}}}}