Name
Abstract | ||
|---|---|---|
In complex pattern recognition tasks, objects are typically characterized by means of multimodality attributes, including categorical, numerical, text, image, audio, and even videos. In these cases, data are usually high dimensional, structurally complex, and granular. Those attributes exhibit some redundancy and irrelevant information. The evaluation, selection, and combination of multimodality a... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TFUZZ.2017.2647966 | IEEE Transactions on Fuzzy Systems |
Keywords | Field | DocType |
Rough sets,Kernel,Algorithm design and analysis,Numerical models,Videos,Computational modeling,Pattern recognition | Data mining,Fuzzy classification,Fuzzy set operations,Fuzzy set,Artificial intelligence,Fuzzy number,Neuro-fuzzy,Defuzzification,Pattern recognition,Rough set,Membership function,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 1 | 1063-6706 |
Citations | PageRank | References |
23 | 0.52 | 27 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qinghua Hu | 1 | 4028 | 171.50 |
| Lingjun Zhang | 2 | 27 | 1.58 |
| Yucan Zhou | 3 | 50 | 8.08 |
| W. Pedrycz | 4 | 13966 | 1005.85 |