DaCapo: a modular deep learning framework for scalable 3D image segmentation
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911979482906624 |
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| author | Patton, William Rhoades, Jeff L. Zouinkhi, Marwan Ackerman, David G. Malin-Mayor, Caroline Adjavon, Diane Heinrich, Larissa Bennett, Davis Zubov, Yurii Team, CellMap Project Weigel, Aubrey V. Funke, Jan |
| author_facet | Patton, William Rhoades, Jeff L. Zouinkhi, Marwan Ackerman, David G. Malin-Mayor, Caroline Adjavon, Diane Heinrich, Larissa Bennett, Davis Zubov, Yurii Team, CellMap Project Weigel, Aubrey V. Funke, Jan |
| contents | DaCapo is a specialized deep learning library tailored to expedite the training and application of existing machine learning approaches on large, near-isotropic image data. In this correspondence, we introduce DaCapo's unique features optimized for this specific domain, highlighting its modular structure, efficient experiment management tools, and scalable deployment capabilities. We discuss its potential to improve access to large-scale, isotropic image segmentation and invite the community to explore and contribute to this open-source initiative. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_02834 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | DaCapo: a modular deep learning framework for scalable 3D image segmentation Patton, William Rhoades, Jeff L. Zouinkhi, Marwan Ackerman, David G. Malin-Mayor, Caroline Adjavon, Diane Heinrich, Larissa Bennett, Davis Zubov, Yurii Team, CellMap Project Weigel, Aubrey V. Funke, Jan Computer Vision and Pattern Recognition Machine Learning Image and Video Processing Quantitative Methods I.4.6 DaCapo is a specialized deep learning library tailored to expedite the training and application of existing machine learning approaches on large, near-isotropic image data. In this correspondence, we introduce DaCapo's unique features optimized for this specific domain, highlighting its modular structure, efficient experiment management tools, and scalable deployment capabilities. We discuss its potential to improve access to large-scale, isotropic image segmentation and invite the community to explore and contribute to this open-source initiative. |
| title | DaCapo: a modular deep learning framework for scalable 3D image segmentation |
| topic | Computer Vision and Pattern Recognition Machine Learning Image and Video Processing Quantitative Methods I.4.6 |
| url | https://arxiv.org/abs/2408.02834 |