Name
Abstract | ||
|---|---|---|
The tree structure is one of the most powerful structures for data organization. An efficient learning framework for transforming tree-structured data into vectorial representations is presented. First, in attempting to uncover the global discriminative information of child nodes hidden at the same level of all of the trees, a clustering technique can be adopted for allocating children into differ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNNLS.2018.2797060 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Vegetation,Image reconstruction,Image representation,Indexes,Self-organizing feature maps,Nonhomogeneous media | Iterative reconstruction,Weighting,Pattern recognition,Computer science,Image retrieval,Artificial intelligence,Concatenation,Tree structure,Cluster analysis,Discriminative model,Recursion | Journal |
Volume | Issue | ISSN |
29 | 11 | 2162-237X |
Citations | PageRank | References |
18 | 0.60 | 27 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haijun Zhang | 1 | 495 | 37.70 |
| Shuang Wang | 2 | 46 | 10.94 |
| Xiaofei Xu | 3 | 408 | 70.26 |
| Tommy W. S. Chow | 4 | 1904 | 141.76 |
| Q. M. Jonathan Wu | 5 | 2457 | 164.07 |