Marginalized Stacked Denoising Autoencoder With Adaptive Noise Probability for Cross Domain Classification
Cross-domain classification is a challenging problem, in which, how to learn domain invariant features is critical. Recently, significant improvements to this problem have emerged with the wide application of deep learning models, which have been proposed to learn higher level and robust feature rep...
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| Veröffentlicht in: | IEEE access Jg. 7; S. 143015 - 143024 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Piscataway
IEEE
2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Schlagworte: | |
| ISSN: | 2169-3536, 2169-3536 |
| Online-Zugang: | Volltext |
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