Cargando…
Autoencoder and Partially Impossible Reconstruction Losses
The generally unsupervised nature of autoencoder models implies that the main training metric is formulated as the error between input images and their corresponding reconstructions. Different reconstruction loss variations and latent space regularizations have been shown to improve model performanc...
| Autores principales: | , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268944/ https://www.ncbi.nlm.nih.gov/pubmed/35808357 http://dx.doi.org/10.3390/s22134862 |