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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17171696 |
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| _version_ | 1866902206256513024 |
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| author | Emmanuel Pio Pastore |
| author_facet | Emmanuel Pio Pastore |
| contents | <p>Archaeology, as a discipline, has only recently begun integrating com- putational tools such as artificial intelligence and numerical simulations into its methodologies. This volume explores the application of modern computational techniques (including convolutional neural networks, va- riational autoencoders, and the stochastic Gray-Scott mathematical mo- del) to the field of industrial archaeology, with a focus on the renowned archaeological site of Sybaris in Calabria. By leveraging these advanced methodologies, clearly explained in an accessible yet rigorous manner, the study aims to demonstrate how arti- ficial intelligence can enhance our socio-cultural understanding of both ancient and modern civilizations. Furthermore, it highlights the potential for optimizing excavation strategies and resource allocation with moderate computational resources and significant economic benefits for archaeolo- gical research. Designed for an audience experienced in archaeology but less familiar with computer science, this volume also provides practical Python scripts, step-by-step implementation guides, and strategic insights into selecting suitable software and hardware for conducting similar studies.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17171696 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Archeologia Neurale Emmanuel Pio Pastore <p>Archaeology, as a discipline, has only recently begun integrating com- putational tools such as artificial intelligence and numerical simulations into its methodologies. This volume explores the application of modern computational techniques (including convolutional neural networks, va- riational autoencoders, and the stochastic Gray-Scott mathematical mo- del) to the field of industrial archaeology, with a focus on the renowned archaeological site of Sybaris in Calabria. By leveraging these advanced methodologies, clearly explained in an accessible yet rigorous manner, the study aims to demonstrate how arti- ficial intelligence can enhance our socio-cultural understanding of both ancient and modern civilizations. Furthermore, it highlights the potential for optimizing excavation strategies and resource allocation with moderate computational resources and significant economic benefits for archaeolo- gical research. Designed for an audience experienced in archaeology but less familiar with computer science, this volume also provides practical Python scripts, step-by-step implementation guides, and strategic insights into selecting suitable software and hardware for conducting similar studies.</p> |
| title | Archeologia Neurale |
| url | https://doi.org/10.5281/zenodo.17171696 |