Robot Semantic Localization Through CNN Descriptors
Semantic localization for mobile robots involves an accurate determination of the kind of place where a robot is located. Therefore, the representation of the knowledge of this place is crucial for the robot. In this paper we present a study for finding a robust model for scene classification proced...
שמור ב:
| מחבר ראשי: | |
|---|---|
| מחברים אחרים: | , |
| פורמט: | article |
| שפה: | אנגלית |
| יצא לאור: |
2020
|
| נושאים: | |
| גישה מקוונת: | https://link.springer.com/chapter/10.1007/978-3-319-70833-1_46 https://ridda2.utp.ac.pa/handle/123456789/9444 |
| תגים: |
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!
|
| _version_ | 1869652471259856896 |
|---|---|
| author | Cruz, Edmanuel |
| author2 | Rangel, José Carlos Cazorla, Miguel |
| author2_role | author author |
| author_browse | Cazorla, Miguel Cruz, Edmanuel Rangel, José Carlos |
| author_facet | Cruz, Edmanuel Rangel, José Carlos Cazorla, Miguel |
| author_role | author |
| collection | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| dc.creator.none.fl_str_mv | Cruz, Edmanuel Rangel, José Carlos Cazorla, Miguel |
| dc.date.none.fl_str_mv | 11/12/2017 11/12/2017 2020-01-02T21:09:02Z 2020-01-02T21:09:02Z 2020-01-02T21:09:02Z 2020-01-02T21:09:02Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://link.springer.com/chapter/10.1007/978-3-319-70833-1_46 978-3-319-70833-1 https://ridda2.utp.ac.pa/handle/123456789/9444 https://ridda2.utp.ac.pa/handle/123456789/9444 |
| dc.language.none.fl_str_mv | eng en |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/embargoedAccess |
| dc.source.none.fl_str_mv | reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP instname:Universidad Tecnológica de Panamá instacron:U Tecnológica de Panamá |
| dc.subject.none.fl_str_mv | Semantic localization Deep Learning Environment perception Image processing Semantic localization Deep Learning Environment perception Image processing |
| dc.title.none.fl_str_mv | Robot Semantic Localization Through CNN Descriptors |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | Semantic localization for mobile robots involves an accurate determination of the kind of place where a robot is located. Therefore, the representation of the knowledge of this place is crucial for the robot. In this paper we present a study for finding a robust model for scene classification procedure for a mobile robot. The proposed system uses CNN descriptors for representing the input perceptions of the robot. First, we develop comparative experiments in order for finding a model. Experiments include the evaluation of several pre-trained CNN models and training a classifier with different classifications algorithms. These experiments were carried out using the ViDRILO dataset and compared with the benchmark provided by their authors. The results demonstrate the goodness of using CNN descriptors for semantic classification. |
| eu_rights_str_mv | embargoedAccess |
| format | article |
| id | lrtest_9902be4f21497568db2f807b6a7d9e0b |
| identifier_str_mv | 978-3-319-70833-1 |
| instacron_str | U Tecnológica de Panamá |
| institution | U Tecnológica de Panamá |
| instname_str | Universidad Tecnológica de Panamá |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | lrtest |
| network_name_str | lr |
| oai_identifier_str | oai:ridda2.utp.ac.pa:123456789/9444 |
| publishDate | 2020 |
| publishDateSort | 2020 |
| reponame_str | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Robot Semantic Localization Through CNN DescriptorsCruz, EdmanuelRangel, José CarlosCazorla, MiguelSemantic localizationDeep LearningEnvironment perceptionImage processingSemantic localizationDeep LearningEnvironment perceptionImage processingSemantic localization for mobile robots involves an accurate determination of the kind of place where a robot is located. Therefore, the representation of the knowledge of this place is crucial for the robot. In this paper we present a study for finding a robust model for scene classification procedure for a mobile robot. The proposed system uses CNN descriptors for representing the input perceptions of the robot. First, we develop comparative experiments in order for finding a model. Experiments include the evaluation of several pre-trained CNN models and training a classifier with different classifications algorithms. These experiments were carried out using the ViDRILO dataset and compared with the benchmark provided by their authors. The results demonstrate the goodness of using CNN descriptors for semantic classification.Semantic localization for mobile robots involves an accurate determination of the kind of place where a robot is located. Therefore, the representation of the knowledge of this place is crucial for the robot. In this paper we present a study for finding a robust model for scene classification procedure for a mobile robot. The proposed system uses CNN descriptors for representing the input perceptions of the robot. First, we develop comparative experiments in order for finding a model. Experiments include the evaluation of several pre-trained CNN models and training a classifier with different classifications algorithms. These experiments were carried out using the ViDRILO dataset and compared with the benchmark provided by their authors. The results demonstrate the goodness of using CNN descriptors for semantic classification.2020-01-02T21:09:02Z2020-01-02T21:09:02Z2020-01-02T21:09:02Z2020-01-02T21:09:02Z11/12/201711/12/2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://link.springer.com/chapter/10.1007/978-3-319-70833-1_46978-3-319-70833-1https://ridda2.utp.ac.pa/handle/123456789/9444https://ridda2.utp.ac.pa/handle/123456789/9444engeninfo:eu-repo/semantics/embargoedAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/94442021-07-06T15:35:09Z |
| spellingShingle | Robot Semantic Localization Through CNN Descriptors Cruz, Edmanuel Semantic localization Deep Learning Environment perception Image processing Semantic localization Deep Learning Environment perception Image processing |
| status_str | publishedVersion |
| title | Robot Semantic Localization Through CNN Descriptors |
| title_full | Robot Semantic Localization Through CNN Descriptors |
| title_fullStr | Robot Semantic Localization Through CNN Descriptors |
| title_full_unstemmed | Robot Semantic Localization Through CNN Descriptors |
| title_short | Robot Semantic Localization Through CNN Descriptors |
| title_sort | Robot Semantic Localization Through CNN Descriptors |
| topic | Semantic localization Deep Learning Environment perception Image processing Semantic localization Deep Learning Environment perception Image processing |
| url | https://link.springer.com/chapter/10.1007/978-3-319-70833-1_46 https://ridda2.utp.ac.pa/handle/123456789/9444 |