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A Pipeline Defect Instance Segmentation System Based on SparseInst
Deep learning algorithms have achieved encouraging results for pipeline defect segmentation. However, existing defect segmentation methods may encounter challenges in accurately segmenting the complex features of pipeline defects and suffer from low processing speeds. Therefore, in this study, we pr...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675068/ https://www.ncbi.nlm.nih.gov/pubmed/38005407 http://dx.doi.org/10.3390/s23229019 |