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AID-U-Net: An Innovative Deep Convolutional Architecture for Semantic Segmentation of Biomedical Images
Semantic segmentation of biomedical images found its niche in screening and diagnostic applications. Recent methods based on deep learning convolutional neural networks have been very effective, since they are readily adaptive to biomedical applications and outperform other competitive segmentation...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777521/ https://www.ncbi.nlm.nih.gov/pubmed/36552959 http://dx.doi.org/10.3390/diagnostics12122952 |