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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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Springer Nature
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/9d943c62d5c046279d89872e62d1ab2c |
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