Certified ML Object Detection for Surveillance Missions
Fuente:
arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914837996503040 |
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| author | Belcaid, Mohammed Bonnafous, Eric Crison, Louis Faure, Christophe Jenn, Eric Pagetti, Claire |
| author_facet | Belcaid, Mohammed Bonnafous, Eric Crison, Louis Faure, Christophe Jenn, Eric Pagetti, Claire |
| contents | In this paper, we present a development process of a drone detection system involving a machine learning object detection component. The purpose is to reach acceptable performance objectives and provide sufficient evidences, required by the recommendations (soon to be published) of the ED 324 / ARP 6983 standard, to gain confidence in the dependability of the designed system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_12362 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Certified ML Object Detection for Surveillance Missions Belcaid, Mohammed Bonnafous, Eric Crison, Louis Faure, Christophe Jenn, Eric Pagetti, Claire Artificial Intelligence In this paper, we present a development process of a drone detection system involving a machine learning object detection component. The purpose is to reach acceptable performance objectives and provide sufficient evidences, required by the recommendations (soon to be published) of the ED 324 / ARP 6983 standard, to gain confidence in the dependability of the designed system. |
| title | Certified ML Object Detection for Surveillance Missions |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2406.12362 |