Abstract
In order to conduct a comprehensive vulnerability analysis of armored vehicles, we developed armored vehicle target vulnerability database software using Visual Studio 2019 software development tool and Sqlite database software. The software consists of modules such as target function and structure analysis, target damage level and damage tree, target equivalence model and target damage criterion, which contain various conditions for vulnerability analysis of armored vehicles and lay the foundation for damage assessment of armored vehicle targets.
Original language | English |
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Title of host publication | Third International Conference on Computer Vision and Data Mining, ICCVDM 2022 |
Editors | Tao Zhang, Ting Yang |
Publisher | SPIE |
ISBN (Electronic) | 9781510661363 |
DOIs | |
Publication status | Published - 2023 |
Externally published | Yes |
Event | 3rd International Conference on Computer Vision and Data Mining, ICCVDM 2022 - Hulun Buir, China Duration: 19 Aug 2022 → 21 Aug 2022 |
Publication series
Name | Proceedings of SPIE - The International Society for Optical Engineering |
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Volume | 12511 |
ISSN (Print) | 0277-786X |
ISSN (Electronic) | 1996-756X |
Conference
Conference | 3rd International Conference on Computer Vision and Data Mining, ICCVDM 2022 |
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Country/Territory | China |
City | Hulun Buir |
Period | 19/08/22 → 21/08/22 |
Keywords
- Armored vehicles
- Databases
- Software design
- Vulnerability
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Liang, Z., Chen, L., Wang, S., & Zhao, H. (2023). Armored vehicle target vulnerability database software design. In T. Zhang, & T. Yang (Eds.), Third International Conference on Computer Vision and Data Mining, ICCVDM 2022 Article 125110A (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 12511). SPIE. https://doi.org/10.1117/12.2660312