Human Activity Recognition using deep learning techniques

Human activity recognition (HAR) is at the forefront of Pervasive Computing efforts, and deep learning techniques currently empower the most successful endeavors within the field. By using a publicly available dataset an exploratory analysis of feature learning is put forward in this work. The convo...

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Autores:
Gómez Meneses, Fabián Andrés
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/69588
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/69588
http://bdigital.unal.edu.co/71559/
Palabra clave:
0 Generalidades / Computer science, information and general works
62 Ingeniería y operaciones afines / Engineering
Machine learning
Deep learning
Human behavior
Neural networks
Pervasive computing
Aprendizaje de máquina
Aprendizaje profundo
Comportamiento humano
Redes neuronales
Computación ubicua
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
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oai_identifier_str oai:repositorio.unal.edu.co:unal/69588
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network_name_str Universidad Nacional de Colombia
repository_id_str
spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2González Osorio, Fabio AugustoGómez Meneses, Fabián Andrés0adba69c-1aeb-49ff-abed-1150431b77f43002019-07-03T10:29:57Z2019-07-03T10:29:57Z2018-10-10https://repositorio.unal.edu.co/handle/unal/69588http://bdigital.unal.edu.co/71559/Human activity recognition (HAR) is at the forefront of Pervasive Computing efforts, and deep learning techniques currently empower the most successful endeavors within the field. By using a publicly available dataset an exploratory analysis of feature learning is put forward in this work. The convolutional neural network deployed here highlights both the advantages and limitations of this class of models, while offering an overview of machine learning-aided human behavior analysis. Furthermore, the exploration includes an experimental comparison with a more traditional SVM model with feature engineering, over the same data.Resumen: El reconocimiento de la Actividad Humana (HAR) está a la vanguardia de los esfuerzos de computación, y las técnicas de aprendizaje profundo actualmente empoderan los esfuerzos más exitosos dentro del campo. Al utilizar un conjunto de datos disponible públicamente. En este trabajo se presenta un análisis exploratorio del aprendizaje de características de la red neuronal convolucional y se destaca tanto las ventajas como las limitaciones de esta clase de modelos, al tiempo que ofrece una visión general de aprendizaje asistido por máquina y análisis del comportamiento humano. Además, la exploración incluye una comparación experimental. con un modelo SVM más tradicional con ingeniería sobre los mismos datos.Maestríaapplication/pdfspaUniversidad Nacional de Colombia Sede Bogotá Facultad de Ingeniería Departamento de Ingeniería de Sistemas e Industrial Ingeniería de SistemasIngeniería de SistemasGómez Meneses, Fabián Andrés (2018) Human Activity Recognition using deep learning techniques. Maestría thesis, Universidad Nacional de Colombia - Sede Bogotá.0 Generalidades / Computer science, information and general works62 Ingeniería y operaciones afines / EngineeringMachine learningDeep learningHuman behaviorNeural networksPervasive computingAprendizaje de máquinaAprendizaje profundoComportamiento humanoRedes neuronalesComputación ubicuaHuman Activity Recognition using deep learning techniquesTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMORIGINALFabianGomez.2018.pdfapplication/pdf792744https://repositorio.unal.edu.co/bitstream/unal/69588/1/FabianGomez.2018.pdf5f66d3861955846845cb774c5fdc1e81MD51THUMBNAILFabianGomez.2018.pdf.jpgFabianGomez.2018.pdf.jpgGenerated Thumbnailimage/jpeg2580https://repositorio.unal.edu.co/bitstream/unal/69588/2/FabianGomez.2018.pdf.jpg595bc0f299371c7a4ed679cdcae7c3fdMD52unal/69588oai:repositorio.unal.edu.co:unal/695882023-06-09 23:03:22.951Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv Human Activity Recognition using deep learning techniques
title Human Activity Recognition using deep learning techniques
spellingShingle Human Activity Recognition using deep learning techniques
0 Generalidades / Computer science, information and general works
62 Ingeniería y operaciones afines / Engineering
Machine learning
Deep learning
Human behavior
Neural networks
Pervasive computing
Aprendizaje de máquina
Aprendizaje profundo
Comportamiento humano
Redes neuronales
Computación ubicua
title_short Human Activity Recognition using deep learning techniques
title_full Human Activity Recognition using deep learning techniques
title_fullStr Human Activity Recognition using deep learning techniques
title_full_unstemmed Human Activity Recognition using deep learning techniques
title_sort Human Activity Recognition using deep learning techniques
dc.creator.fl_str_mv Gómez Meneses, Fabián Andrés
dc.contributor.author.spa.fl_str_mv Gómez Meneses, Fabián Andrés
dc.contributor.spa.fl_str_mv González Osorio, Fabio Augusto
dc.subject.ddc.spa.fl_str_mv 0 Generalidades / Computer science, information and general works
62 Ingeniería y operaciones afines / Engineering
topic 0 Generalidades / Computer science, information and general works
62 Ingeniería y operaciones afines / Engineering
Machine learning
Deep learning
Human behavior
Neural networks
Pervasive computing
Aprendizaje de máquina
Aprendizaje profundo
Comportamiento humano
Redes neuronales
Computación ubicua
dc.subject.proposal.spa.fl_str_mv Machine learning
Deep learning
Human behavior
Neural networks
Pervasive computing
Aprendizaje de máquina
Aprendizaje profundo
Comportamiento humano
Redes neuronales
Computación ubicua
description Human activity recognition (HAR) is at the forefront of Pervasive Computing efforts, and deep learning techniques currently empower the most successful endeavors within the field. By using a publicly available dataset an exploratory analysis of feature learning is put forward in this work. The convolutional neural network deployed here highlights both the advantages and limitations of this class of models, while offering an overview of machine learning-aided human behavior analysis. Furthermore, the exploration includes an experimental comparison with a more traditional SVM model with feature engineering, over the same data.
publishDate 2018
dc.date.issued.spa.fl_str_mv 2018-10-10
dc.date.accessioned.spa.fl_str_mv 2019-07-03T10:29:57Z
dc.date.available.spa.fl_str_mv 2019-07-03T10:29:57Z
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/69588
dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/71559/
url https://repositorio.unal.edu.co/handle/unal/69588
http://bdigital.unal.edu.co/71559/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Sede Bogotá Facultad de Ingeniería Departamento de Ingeniería de Sistemas e Industrial Ingeniería de Sistemas
Ingeniería de Sistemas
dc.relation.references.spa.fl_str_mv Gómez Meneses, Fabián Andrés (2018) Human Activity Recognition using deep learning techniques. Maestría thesis, Universidad Nacional de Colombia - Sede Bogotá.
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
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dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/69588/1/FabianGomez.2018.pdf
https://repositorio.unal.edu.co/bitstream/unal/69588/2/FabianGomez.2018.pdf.jpg
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repository.name.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv repositorio_nal@unal.edu.co
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