Name
Abstract | ||
|---|---|---|
•Method extracts a vectorial embedding representation of image classification tasks.•Method evaluated in a metalearning case study with six CNN algorithms and 45 datasets.•Feature vectors of datasets with similar difficulty are close in the embedding space.•The results overcame the baseline methods in all assessed performance measures.•Meta-learning with Dataset2Vec reached high precision, overcoming image descriptors. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.115053 | Expert Systems with Applications |
Keywords | DocType | Volume |
Dataset embedding,Algorithm selection,Meta-learning,Image dataset description | Journal | 180 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas V. Dias | 1 | 0 | 0.34 |
| Péricles B.C. Miranda | 2 | 0 | 0.34 |
| André C.A. Nascimento | 3 | 0 | 0.34 |
| F. R. Cordeiro | 4 | 46 | 7.14 |
| Rafael Ferreira Mello | 5 | 1 | 2.04 |
| Ricardo B.C Prudêencio | 6 | 0 | 0.34 |