Name
Abstract | ||
|---|---|---|
Smoke detection in foggy surveillance environments is a challenging task and plays a key role in disaster management for industrial systems. The current smoke detection methods are applicable to only normal surveillance videos, providing unsatisfactory results for video streams captured from foggy environments, due to challenges related to clutter and unclear contents. In this paper, an energy-fri... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TII.2019.2915592 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Surveillance,Videos,Image edge detection,Image color analysis,Measurement,Informatics,Disaster management | Computer science,Smoke,Real-time computing | Journal |
Volume | Issue | ISSN |
16 | 2 | 1551-3203 |
Citations | PageRank | References |
10 | 0.49 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khan Muhammad | 1 | 986 | 67.67 |
| Salman Khan | 2 | 387 | 41.05 |
| Vasile Palade | 3 | 1353 | 114.44 |
| Irfan Mehmood | 4 | 522 | 30.84 |
| Victor Hugo C. de Albuquerque | 5 | 914 | 83.30 |