URDD:城市道路疾病检测和分类的开放数据集
Shuaiqi Liu1,2, Wenjing Jiang1,2, Yue Yu1,2
1College of Electronic and Information Engineering, Hebei University, Baoding 071002, China.
Data in brief
|April 14, 2025
概括
这项研究引入了人工智能 (AI) 的新数据集,用于使用深度学习来检测道路疾病,改善城市道路维护和安全.
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:
- 城市交通事故正在增加,原因包括更多的车辆,气候变化和排水不良等因素.
- 目前的道路疾病检测是手动的,耗时的,主观的,依赖于地面透雷达数据分析.
研究的目的:
- 提高道路疾病检测的效率和准确性.
- 促进人工智能 (AI) 在自主道路检查中的应用.
主要方法:
- 利用深度学习,特别是卷积神经网络 (CNN),用于图像识别和对象检测.
- 开发了一套专门的道路疾病数据集,适用于对象检测和分类任务.
主要成果:
- 展示了AI和CNN的潜力,可以显著提高道路疾病检测效率和准确性.
- 创建并发布了一个新的数据集,以促进人工智能驱动的道路维护.
结论:
- 人工智能驱动的道路疾病检测为传统方法提供了更有效和客观的替代方案.
- 新的数据集将加速开发和部署用于城市道路管理的AI解决方案.
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