Discovering fully semantic representations via centroid- and orientation-aware feature learning
Learning meaningful representations of images in scientific domains that are robust to variations in centroids and orientations remains an important challenge. Here we introduce centroid- and orientation-aware disentangling autoencoder (CODAE), an encoder–decoder-based neural network that learns mea...
| Autores principales: | , , , , , , |
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| Formato: | Journal article |
| Lenguaje: | English |
| Publicado: |
Nature Research
2025
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