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Semi-Self-Supervised Learning for Semantic Segmentation in Images with Dense Patterns
Deep learning has shown potential in domains with large-scale annotated datasets. However, manual annotation is expensive, time-consuming, and tedious. Pixel-level annotations are particularly costly for semantic segmentation in images with dense irregular patterns of object instances, such as in pl...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
AAAS
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013790/ https://www.ncbi.nlm.nih.gov/pubmed/36930764 http://dx.doi.org/10.34133/plantphenomics.0025 |