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A U-Net Based Approach for Automating Tribological Experiments
Tribological experiments (i.e., characterizing the friction and wear behavior of materials) are crucial for determining their potential areas of application. Automating such tests could hence help speed up the development of novel materials and coatings. Here, we utilize convolutional neural network...
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| Publicado en: | Sensors (Basel) |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7700163/ https://ncbi.nlm.nih.gov/pubmed/33238554 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20226703 |
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