Name
Title | ||
|---|---|---|
Generative Adversarial Networks and Markov Random Fields for oversampling very small training sets |
Abstract | ||
|---|---|---|
•A new method for oversampling very scarce training sets.•Based on Generative Adversarial Networks and Markov Random Field models.•Much better performance than SMOTE on simulated and real data experiment. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2020.113819 | Expert Systems with Applications |
Keywords | DocType | Volume |
Classifier training,Oversampling,Generative adversarial networks,Markov random fields | Journal | 163 |
ISSN | Citations | PageRank |
0957-4174 | 3 | 0.46 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Addisson Salazar | 1 | 121 | 23.46 |
| L. Vergara | 2 | 68 | 18.45 |
| Gonzalo Safont | 3 | 54 | 12.55 |