Name
Title | ||
|---|---|---|
Estimation of critical parameters in concrete production using multispectral vision technology |
Abstract | ||
|---|---|---|
We analyze multispectral reflectance images of concrete aggregate material, and design computational measures of the important and critical parameters used in concrete production. The features extracted from the images are exploited as explanatory variables in regression models and used to predict aggregate type, water content, and size distribution. We analyze and validate the methods on five representative aggregate types, commonly used in concrete production. Using cross validation, the generated models proves to have a high performance in predicting all of the critical parameters. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11499145_124 | SCIA |
Keywords | Field | DocType |
multispectral vision technology,concrete production,critical parameter,multispectral reflectance image,aggregate type,design computational measure,representative aggregate type,concrete aggregate material,high performance,cross validation,explanatory variable,feature extraction,regression model,water content | Pattern recognition,Regression analysis,Computer science,Multispectral image,Image processing,Artificial intelligence,Estimation theory,Aggregate (composite),System identification,Reflectivity,Cross-validation | Conference |
Volume | ISSN | ISBN |
3540 | 0302-9743 | 3-540-26320-9 |
Citations | PageRank | References |
1 | 0.41 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael E. Hansen | 1 | 8 | 1.90 |
| Bjarne Ersbøll | 2 | 450 | 38.06 |
| Jens Michael Carstensen | 3 | 83 | 14.27 |
| Allan A. Nielsen | 4 | 15 | 2.28 |