用于培训神经网络在混凝土裂检测中的数据集:实验室分类的梁和柱形图像
Alexandre Almeida Del Savio1, Ana Luna Torres1, Daniel Cárdenas-Salas2
1Carrera de Ingeniería Civil, Instituto de Investigación Científica, Universidad de Lima, Lima, Perú.
Data in brief
|June 16, 2025
概括
研究人员开发了一个新的数据集,包括1132个混凝土裂图像,用于训练人工智能 (AI) 模型. 该资源有助于为建筑行业开发自动化结构健康监测系统.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 建筑行业正在整合人工智能 (AI) 以加强结构分析和监测.
- 获得高质量的数据集用于训练人工智能模型以检测混凝土裂是一个重大的挑战,因为它们在现实环境下逐渐发展.
研究的目的:
- 引入一个精心策划的混凝土裂图像数据集,以促进基于人工智能的计算机视觉模型的开发和验证,用于自动化裂检测.
- 支持结构工程的研究,并推进自动化结构健康监测.
主要方法:
- 创建了一个数据集,包括1132个手工分类的图像,显示梁和柱子中的混凝土裂.
- 图像是在受控的实验室环境中使用静态IP摄像头捕获的.
- 使用LabelImg工具进行图像注释,为不同的裂和故障定义了五个对象类.
主要成果:
- 该数据集包括1,132张图像与结构部件中的混凝土裂的手动分类.
- 每个图像都附带.txt文件,包含五个不同的对象类的分类和坐标数据.
- 数据集的结构使得基于神经网络的计算机视觉模型的培训和验证成为可能.
结论:
- 这个精心策划的数据集是结构工程研究人员的宝贵资源,专注于自动裂检测.
- 它促进了用于结构性健康监测的更准确和更有效的AI模型的开发.
- 该数据集有助于在建筑行业更广泛地采用人工智能,以提高安全性和维护.
关键词:
建筑工程中的人工智能计算机视觉 计算机视觉 计算机视觉混凝土梁是混凝土梁的一种.混凝土柱子是指混凝土柱子.混凝土裂检测 混凝土裂检测图像分类数据集 图像分类数据集神经网络的神经网络的神经网络结构性健康监测 结构性健康监测更多相关视频
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