Name
Abstract | ||
|---|---|---|
Synthetic aperture radar (SAR) automatic target recognition (ATR) plays an important role in SAR image interpretation. However, at least hundreds of training samples are usually required for each target type in the existing SAR ATR algorithms. In this article, a novel few-shot learning framework named hybrid inference network (HIN) is proposed to tackle the problem of SAR target recognition with o... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2021.3051024 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Training,Synthetic aperture radar,Target recognition,Task analysis,Radar polarimetry,Manifolds,Feature extraction | Journal | 59 |
Issue | ISSN | Citations |
11 | 0196-2892 | 1 |
PageRank | References | Authors |
0.36 | 0 | 4 |