Name
Title | ||
|---|---|---|
DecomVQANet: Decomposing visual question answering deep network via tensor decomposition and regression |
Abstract | ||
|---|---|---|
•An optimal compression and acceleration solution for Visual Question Answering systems.•The method reduces parameters about 80% while performance only drops 1%.•The algorithm is a paradigm which can be widely used on most mobile devices. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.patcog.2020.107538 | Pattern Recognition |
Keywords | DocType | Volume |
Tensor decomposition,Tensor regression layer,Tensor contraction layer,Visual question answering | Journal | 110 |
Issue | ISSN | Citations |
1 | 0031-3203 | 1 |
PageRank | References | Authors |
0.40 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zongwen Bai | 1 | 8 | 5.28 |
| Ying Li | 2 | 130 | 21.36 |
| Marcin Wozniak | 3 | 36 | 13.22 |
| Meili Zhou | 4 | 1 | 0.40 |
| Di Li | 5 | 1 | 0.73 |