Convolutional neural network approach for the automated identification of in cellulo crystals
de Diego Martinez, Inaki; Kardoost, Amirhossein;
Convolutional neural network approach for the automated identification of in cellulo crystals
This repository contains all files required to complement our manuscript entitled "Convolutional neural network approach for the automated identification of in cellulo crystals" published in the Journal of Applied Crystallography (A. Kardoost, R. Schönherr, C. Deiter, L. Redecke, K. Lorenzen, J. Schulz and I. de Diego (2024). J.Appl. Cryst. 57, https://doi.org/10.1107/S1600576724000682). In this work we make use of Mask R-CNN, a Convolutional Neural Network (CNN) based instance segmentation method, for the identification of crystals growing in living insect cells, using conventional bright field images.
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selected citations
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
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