Self-Supervised Latent Space Optimization With Nebula Variational Coding

Deep learning approaches process data in a layer-by-layer way with intermediate (or latent) features. We aim at designing a general solution to optimize the latent manifolds to improve the performance on classification, segmentation, completion and/or reconstruction through probabilistic models. Thi...

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Publié dans:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 3 vom: 22. März, Seite 1397-1411
Auteur principal:	Wang, Yida (Auteur)
Autres auteurs:	Tan, David Joseph, Navab, Nassir, Tombari, Federico
Format:	Article en ligne
Langue:	English
Publié:	2024
Accès à la collection:	IEEE transactions on pattern analysis and machine intelligence
Sujets:	Journal Article