.png){kind=icon}
返回
Class Shared Dictionary Learning for Few-Shot Remote Sensing Scene Classification
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2022.3180791.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In the field of remote sensing, it is infeasible to collect a large number of labeled samples due to imaging equipment and imaging environment. Few-shot learning (FSL) is the dominant method to alleviate this problem, which pursues quickly adapting to novel categories from a limited number of labeled samples. The few-shot remote sensing scene classification (RSSC) generally includes the pretraining and meta-test phases. However, a negative transfer problem exists that data categories in both the phases are different. It causes the pretrained feature extractor to be unable well-adapted to the novel data category. This letter proposes class shared dictionary learning (CSDL) for few-shot RSSC to address this issue. Specifically, this letter designs the mirror-based feature extractor (MFE) in the pretraining phase, constructing a self-supervised classification task to improve the feature extractor robustness. Furthermore, this letter proposes a class shared dictionary (CSD) classifier based on dictionary learning. The CSD projects the novel data feature in meta-test into subspace to reconstruct more discriminative features and complete the classification task. Extensive experiments on remote sensing datasets have demonstrated that the proposed CSDL achieves advanced classification performance.
Keyword:
Feature extraction
Task analysis
Remote sensing
Image analysis
Dictionaries
Training
Data mining
Dictionary learning
few-shot learning (FSL)
remote sensing scene classification (RSSC)
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
分享收藏Synthesis of a new fluorelastomer from tetrafluoroethylene and propylene by radiation processing
PREAI
分享收藏Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.png)
Cancer Cell
OAAI
Cancer CellIF0
OAAI分享收藏Service-Related Exposures and Physical Health Trajectories Among Aging Veteran Men老年退伍军人中与服务相关的暴露和身体健康轨迹
OAAI
OAAI分享收藏An Investigation of the Mechanical, Thermal and Electrical Properties of an AA7075 Alloy Reinforced with Hybrid Ceramic Nanoparticles Using Friction Stir ProcessingMetalsOAAI
MetalsIF0
OAAI分享收藏Thermally induced crystal-to-crystal transformations accompanied by changes in the magnetic properties of a CuII-p-hydroquinonate polymerCrystEngComm
CrystEngCommIF0
PREAI
分享收藏
查看更多内容