Name
Abstract | ||
|---|---|---|
Thermal cameras can capture images invariant to illumination conditions. However, thermal facial images are difficult to be recognized by human examiners. In this letter, an end-to-end framework, which consists of a generative network and a detector network, is proposed to translate thermal facial images into visible ones. The generative network aims at generating visible images given the thermal ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LSP.2018.2845692 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Detectors,Face recognition,Mathematical model,Gallium nitride,Training,Shape,Visualization | Image translation,Thermal,Pattern recognition,Invariant (mathematics),Artificial intelligence,Generative grammar,Detector,Mathematics,Adversarial system | Journal |
Volume | Issue | ISSN |
25 | 8 | 1070-9908 |
Citations | PageRank | References |
4 | 0.46 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongling Wang | 1 | 4 | 0.46 |
| Zhenzhong Chen | 2 | 1244 | 101.41 |
| Feng Wu | 3 | 3635 | 295.09 |