Drone/Bird Classification Based on Features of Tracks Trajectories
This paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable r...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://depot.sorbonne.ae/handle/20.500.12458/1407 |
| الوسوم: |
إضافة وسم
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| _version_ | 1857415064828510208 |
|---|---|
| author | Kengeskanov, Maksat |
| author2 | Seghrouchni, Amal El Fallah Abu Zitar, Raed Barbaresco, Frederic |
| author2_role | author author author |
| author_facet | Kengeskanov, Maksat Seghrouchni, Amal El Fallah Abu Zitar, Raed Barbaresco, Frederic |
| author_role | author |
| dc.creator.none.fl_str_mv | Kengeskanov, Maksat Seghrouchni, Amal El Fallah Abu Zitar, Raed Barbaresco, Frederic |
| dc.date.none.fl_str_mv | 2023-05-22T04:50:24Z 2023-05-22T04:50:24Z 2023 |
| dc.identifier.none.fl_str_mv | https://depot.sorbonne.ae/handle/20.500.12458/1407 10.1109/AERO55745.2023.10115762 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | 2023 IEEE Aerospace Conference |
| dc.subject.none.fl_str_mv | Support vector machines Image recognition Kinematics Feature extraction Trajectory Reliability Task analysis |
| dc.title.none.fl_str_mv | Drone/Bird Classification Based on Features of Tracks Trajectories |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::conference object::conference proceedings |
| description | This paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable recognition task. Standard Machine Learning methods such as SVM and Random Forest are used for learning this classification. Features based on the kinematics, Gabor filter, and Gray Level Co-occurrence Matrix are utilized. Several comparisons and experiments based on benchmark data sets are show |
| id | sorbonner_7f4599b963476f27a03de8cd22569c28 |
| identifier_str_mv | 10.1109/AERO55745.2023.10115762 |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1407 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Drone/Bird Classification Based on Features of Tracks TrajectoriesKengeskanov, MaksatSeghrouchni, Amal El FallahAbu Zitar, RaedBarbaresco, FredericSupport vector machinesImage recognitionKinematicsFeature extractionTrajectoryReliabilityTask analysisThis paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable recognition task. Standard Machine Learning methods such as SVM and Random Forest are used for learning this classification. Features based on the kinematics, Gabor filter, and Gray Level Co-occurrence Matrix are utilized. Several comparisons and experiments based on benchmark data sets are show2023-05-22T04:50:24Z2023-05-22T04:50:24Z2023Controlled Vocabulary for Resource Type Genres::text::conference object::conference proceedingshttps://depot.sorbonne.ae/handle/20.500.12458/140710.1109/AERO55745.2023.10115762en2023 IEEE Aerospace Conferenceoai:depot.sorbonne.ae:20.500.12458/14072024-03-07T14:47:39Z |
| spellingShingle | Drone/Bird Classification Based on Features of Tracks Trajectories Kengeskanov, Maksat Support vector machines Image recognition Kinematics Feature extraction Trajectory Reliability Task analysis |
| title | Drone/Bird Classification Based on Features of Tracks Trajectories |
| title_full | Drone/Bird Classification Based on Features of Tracks Trajectories |
| title_fullStr | Drone/Bird Classification Based on Features of Tracks Trajectories |
| title_full_unstemmed | Drone/Bird Classification Based on Features of Tracks Trajectories |
| title_short | Drone/Bird Classification Based on Features of Tracks Trajectories |
| title_sort | Drone/Bird Classification Based on Features of Tracks Trajectories |
| topic | Support vector machines Image recognition Kinematics Feature extraction Trajectory Reliability Task analysis |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1407 |