3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates - Phase 2
| 项目名称： | 3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates - Phase 2 |
| 摘要： | Riprap rock and large-sized aggregates have been used extensively in geotechnical and hydraulic engineering to armor shorelines, streambeds, bridge abutments, pilings and other shoreline structures against scour and water or ice erosion. They provide erosion control, sediment control, and scour protection. The sustainable and reliable use of riprap materials demands efficient and accurate evaluation of their large particle sizes, shapes, and gradation information at both quarry production lines and construction sites. The objective of this research project is to develop an advanced non-intrusive machine vision system for field evaluation of riprap aggregates, whereby engineers can obtain 3D size and shape information of individual particles in a riprap stockpile simply by taking videos/images with mobile devices such as smartphone camera. |
| 状态： | Active |
| 资金： | 390000 |
| 资助组织： | Illinois Department of Transportation |
| 开始时间： | 20200701 |
| 预计完成日期： | 20220630 |
| 主题领域： | Data and Information Technology；Highways；Materials；Pavements |
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