Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition

Supplementary files for the publication: Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition

DOI: 10.15490/fairdomhub.1.investigation.281.1

Zenodo URL: None

Created at: 14th Mar 2019 at 11:12

Contents

Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition

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Images of mineral colonization

Images used for training and validation of deep learning algorithm to determine biofilm composition of mixed species biofilms on mineral grains

images_deep_learning_Biotechnology_Reports.zip

Code for image analyses

Archive contains python scripts for image analysis

TF_code.zip

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MD5: 944b6c3f4685ebf49dac5d971b3f2fc9

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Citation

Herold, M., & Buetti-Dinh, A. (2019). Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition. FAIRDOMHub. https://doi.org/10.15490/FAIRDOMHUB.1.INVESTIGATION.281.1

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Created: 14th Mar 2019 at 11:12

Last updated: 14th Mar 2019 at 11:26

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Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition

Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition

Imaging of leaching cultures

Images of mineral colonization

Code for image analysis

Code for image analyses