Armored vehicle target vulnerability database software design

Zhengang Liang, Lidan Chen, Shushan Wang, Hongzhi Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationThird International Conference on Computer Vision and Data Mining, ICCVDM 2022
EditorsTao Zhang, Ting Yang
PublisherSPIE
ISBN (Electronic)9781510661363
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event3rd International Conference on Computer Vision and Data Mining, ICCVDM 2022 - Hulun Buir, China
Duration: 19 Aug 202221 Aug 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12511
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference3rd International Conference on Computer Vision and Data Mining, ICCVDM 2022
Country/TerritoryChina
CityHulun Buir
Period19/08/2221/08/22

Keywords

  • Armored vehicles
  • Databases
  • Software design
  • Vulnerability

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