Name
Title | ||
|---|---|---|
A Building Roof Identification Cnn Based On Interior-Edge-Adjacency Features Using Hyperspectral Imagery |
Abstract | ||
|---|---|---|
Hyperspectral remote sensing can obtain both spatial and spectral information of ground objects. It is an important prerequisite for a hyperspectral remote sensing application to make good use of spectral and image features. Therefore, we improved the Convolutional Neural Network (CNN) model by extracting interior-edge-adjacency features of building roof and proposed a new CNN model with a flexible structure: Building Roof Identification CNN (BRI-CNN). Our experimental results demonstrated that the BRI-CNN can not only extract interior-edge-adjacency features of building roof, but also change the weight of these different features during the training process, according to selected samples. Our approach was tested using the Indian Pines (IP) data set and our comparative study indicates that the BRI-CNN model achieves at least 0.2% higher overall accuracy than that of the capsule network model, and more than 2% than that of CNN models. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.3390/rs13152927 | REMOTE SENSING |
Keywords | DocType | Volume |
hyperspectral image, spectral and spatial feature, Convolutional Neural Network (CNN), interior-edge-adjacency features, building roof | Journal | 13 |
Issue | Citations | PageRank |
15 | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chengming Ye | 1 | 5 | 3.62 |
| Hongfu Li | 2 | 0 | 0.34 |
| Chunming Li | 3 | 0 | 0.34 |
| Xin Liu | 4 | 0 | 0.34 |
| Yao Li | 5 | 0 | 0.34 |
| Jonathan Li | 6 | 798 | 119.18 |
| Wesley Nunes Gonçalves | 7 | 12 | 11.51 |
| José Marcato Junior | 8 | 0 | 4.06 |