Name
Abstract | ||
|---|---|---|
AbstractWe focus on the issue of cloud detection in wireless sensor networks (WSN) and propose a novel detection algorithm named adaptive graph cut (AGC) to tackle this issue. We first automatically label some pixels as "cloud" or "clear sky" with high confidence. Then, those labelled pixels serve as hard constraint seeds for the following graph cut algorithm. In addition, a novel transfer learning algorithmis proposed to transfer knowledge among sensor nodes, such that cloud images captured from different sensor nodes can adapt to different weather conditions. The experimental results show that the proposed algorithm not only achieves better results than other state-of-the-art cloud detection algorithms in WSN, but also achieves comparable results compared with the interactive segmentation algorithm. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1155/2015/947169 | Periodicals |
Field | DocType | Volume |
Cut,Key distribution in wireless sensor networks,Cloud detection,Segmentation,Computer science,Transfer of learning,Computer network,Pixel,Wireless sensor network,Distributed computing,Cloud computing | Journal | 2015 |
Issue | ISSN | Citations |
1 | 1550-1329 | 0 |
PageRank | References | Authors |
0.34 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuang Liu | 1 | 26 | 11.35 |
| Zhongfei (Mark) Zhang | 2 | 2451 | 164.30 |