A deep-learning model for predictive archaeology and archaeological community detection

Abstract Deep learning is a powerful tool for exploring large datasets and discovering new patterns. This work presents an account of a metric learning-based deep convolutional neural network (CNN) applied to an archaeological dataset. The proposed account speaks of three stages: training, testing/v...

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Autores principales: Abraham Resler, Reuven Yeshurun, Filipe Natalio, Raja Giryes
Formato: article
Lenguaje:EN
Publicado: Springer Nature 2021
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Acceso en línea:https://doaj.org/article/9d943c62d5c046279d89872e62d1ab2c
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