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A novel kernel Wasserstein distance on Gaussian measures: an application of identifying dental artifacts in head and neck computed tomography
The Wasserstein distance is a powerful metric based on the theory of optimal mass transport. It gives a natural measure of the distance between two distributions with a wide range of applications. In contrast to a number of the common divergences on distributions such as Kullback-Leibler or Jensen-S...
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| Publicado no: | Comput Biol Med |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7237301/ https://ncbi.nlm.nih.gov/pubmed/32217284 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.compbiomed.2020.103731 |
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