Name
Abstract | ||
|---|---|---|
Context representations have been widely used to profit semantic image segmentation. The emergence of depth data provides additional information to construct more discriminating context representations. Depth data preserves the geometric relationship of objects in a scene, which is generally hard to be inferred from RGB images. While deep convolutional neural networks (CNNs) have been successful i... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCYB.2018.2885062 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Image segmentation,Semantics,Switches,Image color analysis,Image resolution,Computer architecture,Cybernetics | Pattern recognition,Convolutional neural network,Segmentation,Semantic image segmentation,RGB color model,Artificial intelligence,Image structure,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
50 | 3 | 2168-2267 |
Citations | PageRank | References |
10 | 0.47 | 31 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Di Lin | 1 | 16 | 2.95 |
| Ruimao Zhang | 2 | 325 | 18.86 |
| Yuanfeng Ji | 3 | 13 | 1.52 |
| Ping Li | 4 | 202 | 40.76 |
| Hui Huang | 5 | 694 | 52.19 |