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janelia7_blocks-janelia7_biblio_header | block
arXiv. 2024 Aug 05;. doi: 10.48550/arXiv.2408.02834
DaCapo: a modular deep learning framework for scalable 3D image segmentation Funke LabCellMapScientific Computing Software

Patton W, Rhoades JL, Zouinkhi M, Ackerman DG, Malin-Mayor C, Adjavon D, Heinrich L, Bennett D, Zubov Y, Team CP, Weigel A, Funke J
janelia7_blocks-janelia7_biblio_abstract | block
Abstract
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.
janelia7_blocks-janelia7_biblio_authors | block
Janelia Authors
janelia7_blocks-janelia7_biblio_tools | block