MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks
Abstract We present an air-to-air multi-sensor and multi-view fixed-wing UAV dataset, MMFW-UAV, in this work. MMFW-UAV contains a total of 147,417 fixed-wing UAVs images captured by multiple types of sensors (zoom, wide-angle, and thermal imaging sensors), displaying the flight status of fixed-wing...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04482-2 |
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| _version_ | 1832572005148262400 |
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| author | Yang Liu Zhihao Sun Lele Xi Lele Zhang Wei Dong Chen Chen Maobin Lu Hailing Fu Fang Deng |
| author_facet | Yang Liu Zhihao Sun Lele Xi Lele Zhang Wei Dong Chen Chen Maobin Lu Hailing Fu Fang Deng |
| author_sort | Yang Liu |
| collection | DOAJ |
| description | Abstract We present an air-to-air multi-sensor and multi-view fixed-wing UAV dataset, MMFW-UAV, in this work. MMFW-UAV contains a total of 147,417 fixed-wing UAVs images captured by multiple types of sensors (zoom, wide-angle, and thermal imaging sensors), displaying the flight status of fixed-wing UAVs of different sizes, appearances, structures, and stabilized flight velocities from multiple aerial perspectives (top-down, horizontal, and bottom-up views), aiming to cover the full-range of perspectives with multi-modal image data. Quality control processes of semi-automatic annotation, manual check, and secondary refinement are performed on each image. To the best of our knowledge, MMFW-UAV is the first one-to-one multi-modal image dataset for fixed-wing UAVs with high-quality annotations. Several mainstream deep learning-based object detection architectures are evaluated on MMFW-UAV and the experimental results demonstrate that MMFW-UAV can be utilized for fixed-wing UAV identification, detection, and monitoring. We believe that MMFW-UAV will contribute to various fixed-wing UAVs-based research and applications. |
| format | Article |
| id | doaj-art-66959d9eb1f54c66a8ac43b5c3c1a52f |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-66959d9eb1f54c66a8ac43b5c3c1a52f2025-02-02T12:08:12ZengNature PortfolioScientific Data2052-44632025-01-0112111210.1038/s41597-025-04482-2MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasksYang Liu0Zhihao Sun1Lele Xi2Lele Zhang3Wei Dong4Chen Chen5Maobin Lu6Hailing Fu7Fang Deng8National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologySchool of Electrical Engineering, Hebei University of Science and TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyNational Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of TechnologyAbstract We present an air-to-air multi-sensor and multi-view fixed-wing UAV dataset, MMFW-UAV, in this work. MMFW-UAV contains a total of 147,417 fixed-wing UAVs images captured by multiple types of sensors (zoom, wide-angle, and thermal imaging sensors), displaying the flight status of fixed-wing UAVs of different sizes, appearances, structures, and stabilized flight velocities from multiple aerial perspectives (top-down, horizontal, and bottom-up views), aiming to cover the full-range of perspectives with multi-modal image data. Quality control processes of semi-automatic annotation, manual check, and secondary refinement are performed on each image. To the best of our knowledge, MMFW-UAV is the first one-to-one multi-modal image dataset for fixed-wing UAVs with high-quality annotations. Several mainstream deep learning-based object detection architectures are evaluated on MMFW-UAV and the experimental results demonstrate that MMFW-UAV can be utilized for fixed-wing UAV identification, detection, and monitoring. We believe that MMFW-UAV will contribute to various fixed-wing UAVs-based research and applications.https://doi.org/10.1038/s41597-025-04482-2 |
| spellingShingle | Yang Liu Zhihao Sun Lele Xi Lele Zhang Wei Dong Chen Chen Maobin Lu Hailing Fu Fang Deng MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks Scientific Data |
| title | MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks |
| title_full | MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks |
| title_fullStr | MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks |
| title_full_unstemmed | MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks |
| title_short | MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks |
| title_sort | mmfw uav dataset multi sensor and multi view fixed wing uav dataset for air to air vision tasks |
| url | https://doi.org/10.1038/s41597-025-04482-2 |
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