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Found 4 papers, 1 papers with code
Self-Normalized Density Map (SNDM) for Counting Microbiological Objects
The statistical properties of the density map (DM) approach to counting microbiological objects on images are studied in detail.
Generation of microbial colonies dataset with deep learning style transfer
We introduce an effective strategy to generate an annotated synthetic dataset of microbiological images of Petri dishes that can be used to train deep learning models in a fully supervised fashion.
Deep neural networks approach to microbial colony detection -- a comparative analysis
Counting microbial colonies is a fundamental task in microbiology and has many applications in numerous industry branches.
AGAR a microbial colony dataset for deep learning detection
The Annotated Germs for Automated Recognition (AGAR) dataset is an image database of microbial colonies cultured on agar plates.
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