Name
Title | ||
|---|---|---|
Revisiting Graph Convolutional Networks with Mini-Batch Sampling for Hyperspectral Image Classification |
Abstract | ||
|---|---|---|
Graph convolutional networks (GCNs) have been successfully and widely applied in computer vision and machine learning fields. As a powerful tool, GCNs have recently received increasing attention in the remote sensing community, e.g., hyperspectral image (HSI) classification. However, the application ability of GCNs in identifying the materials via spectral signatures remains limited, since traditi... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/WHISPERS52202.2021.9484014 | 2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) |
Keywords | DocType | ISBN |
Convolutional codes,Convolution,Conferences,Machine learning,Tools,Network architecture,Feature extraction | Conference | 978-1-6654-3601-4 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Danfeng Hong | 1 | 0 | 0.34 |
| Lianru Gao | 2 | 373 | 59.90 |
| Xin Wu | 3 | 16 | 3.89 |
| Jing Yao | 4 | 0 | 0.34 |
| Bing Zhang | 5 | 2 | 2.71 |