Name
Abstract | ||
|---|---|---|
•The letter proposes deep CNN models for facial age estimation.•It opens the door for the use of robust loss functions in Deep CNNs.•Empirical evaluations are provided on four public datasets.•The Adpative loss function seems to be a promising loss function. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2019.112942 | Expert Systems with Applications |
Keywords | Field | DocType |
Age estimation from facial images,Deep convolutional neural networks,Robust loss functions,Fine tuning,Regression | Regression,Computer science,Convolutional neural network,Outlier,Mean squared error,Robust regression,Artificial intelligence,Empirical research,Machine learning | Journal |
Volume | ISSN | Citations |
141 | 0957-4174 | 2 |
PageRank | References | Authors |
0.39 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fadi Dornaika | 1 | 809 | 96.43 |
| salah eddine bekhouche | 2 | 32 | 3.64 |
| Ignacio Arganda-Carreras | 3 | 71 | 8.02 |