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Unsupervised feature extraction of aerial images for clustering and understanding hazardous road segments
Aerial image data are becoming more widely available, and analysis techniques based on supervised learning are advancing their use in a wide variety of remote sensing contexts. However, supervised learning requires training datasets which are not always available or easy to construct with aerial ima...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322896/ https://www.ncbi.nlm.nih.gov/pubmed/37407750 http://dx.doi.org/10.1038/s41598-023-38100-1 |