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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2501.07859 |
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| _version_ | 1866929675182276608 |
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| author | Wilkinson, Andrew Keith |
| author_facet | Wilkinson, Andrew Keith |
| contents | deepTerra is a comprehensive platform designed to facilitate the classification of land surface features using machine learning and satellite imagery. The platform includes modules for data collection, image augmentation, training, testing, and prediction, streamlining the entire workflow for image classification tasks. This paper presents a detailed overview of the capabilities of deepTerra, shows how it has been applied to various research areas, and discusses the future directions it might take. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07859 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | deepTerra -- AI Land Classification Made Easy Wilkinson, Andrew Keith Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning deepTerra is a comprehensive platform designed to facilitate the classification of land surface features using machine learning and satellite imagery. The platform includes modules for data collection, image augmentation, training, testing, and prediction, streamlining the entire workflow for image classification tasks. This paper presents a detailed overview of the capabilities of deepTerra, shows how it has been applied to various research areas, and discusses the future directions it might take. |
| title | deepTerra -- AI Land Classification Made Easy |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2501.07859 |