Name
Title | ||
|---|---|---|
A Bayesian-Network-Based Classification Method Integrating Airborne LiDAR Data With Optical Images |
Abstract | ||
|---|---|---|
Point cloud classification is of great importance to applications of airborne Light Detection And Ranging (LiDAR) data. In recent years, airborne LiDAR has been integrated with various other sensors, e.g., optical imaging sensors, and thus, the fusion of multiple data types for scene classification has become a hot topic. Therefore, this paper proposes a Bayesian network (BN) model that is suitabl... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSTARS.2016.2628775 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Three-dimensional displays,Feature extraction,Laser radar,Bayes methods,Vegetation mapping,Optical imaging,Optical sensors | Computer vision,Vegetation,Remote sensing,Feature extraction,Bayesian network,Lidar,Ranging,Artificial intelligence,Point cloud,Classifier (linguistics),Optical imaging,Mathematics | Journal |
Volume | Issue | ISSN |
10 | 4 | 1939-1404 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhizhong Kang | 1 | 55 | 9.15 |
| Juntao Yang | 2 | 1 | 0.35 |
| Ruofei Zhong | 3 | 45 | 18.76 |