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A Convolutional Autoencoder Topology for Classification in High-Dimensional Noisy Image Datasets
Deep convolutional neural networks have shown remarkable performance in the image classification domain. However, Deep Learning models are vulnerable to noise and redundant information encapsulated into the high-dimensional raw input images, leading to unstable and unreliable predictions. Autoencode...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8622369/ https://www.ncbi.nlm.nih.gov/pubmed/34833805 http://dx.doi.org/10.3390/s21227731 |