Title | ||
---|---|---|
Deep Multiple Instance Learning-Based Spatial-Spectral Classification for PAN and MS Imagery. |
Abstract | ||
---|---|---|
Panchromatic (PAN) and multispectral (MS) imagery classification is one of the hottest topics in the field of remote sensing. In recent years, deep learning techniques have been widely applied in many areas of image processing. In this paper, an end-to-end learning framework based on deep multiple instance learning (DMIL) is proposed for MS and PAN images' classification using the joint spectral a... |
Year | DOI | Venue |
---|---|---|
2018 | 10.1109/TGRS.2017.2750220 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Feature extraction,Spatial resolution,Machine learning,Neural networks,Convolution,Fuses | Spatial analysis,Computer vision,Autoencoder,Pattern recognition,Convolutional neural network,Computer science,Multispectral image,Image processing,Feature extraction,Artificial intelligence,Deep learning,Artificial neural network | Journal |
Volume | Issue | ISSN |
56 | 1 | 0196-2892 |
Citations | PageRank | References |
6 | 0.40 | 33 |
Authors | ||
8 |
Name | Order | Citations | PageRank |
---|---|---|---|
X.L. Liu | 1 | 11 | 11.83 |
Licheng Jiao | 2 | 5698 | 475.84 |
Jiaqi Zhao | 3 | 97 | 10.63 |
Jin Zhao | 4 | 46 | 3.90 |
Dan Zhang | 5 | 97 | 21.44 |
Fang Liu | 6 | 1188 | 125.46 |
Shuyuan Yang | 7 | 509 | 48.76 |
Xu Tang | 8 | 20 | 4.68 |