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bioRxiv · 10.1101/2020.03.26.010660

CDeep3M-Preview: Online segmentation using the deep neural network model zoo

Abstract

Sharing deep neural networks and testing the performance of trained networks typically involves a major initial commitment towards one algorithm, before knowing how the network will perform on a different dataset. Here we release a free online tool, CDeep3M-Preview, that allows end-users to rapidly test the performance of any of the pre-trained neural network models hosted on the CIL-CDeep3M modelzoo. This feature makes part of a set of complementary strategies we employ to facilitate sharing, increase reproducibility and enable quicker insights into biology. Namely we: (1) provide CDeep3M deep learning image segmentation software through cloud applications (Colab and AWS) and containerized installations (Docker and Singularity) (2) co-hosting trained deep neural networks with the relevant microscopy images and (3) providing a CDeep3M-Preview feature, enabling quick tests of trained networks on user provided test data or any of the publicly hosted large datasets. The CDeep3M-modelzoo and the cellimagelibrary.org are open for contributions of both, trained models as well as image datasets by the community and all services are free of charge.

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BibTeXRIS

Haberl, M. G., Wong, W., Penticoff, S., Je, J., Madany, M., Borchardt, A., Boassa, D., Peltier, S., Ellisman, M. H.. 2020-03-26. CDeep3M-Preview: Online segmentation using the deep neural network model zoo. https://doi.org/10.1101/2020.03.26.010660

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