Counting and classification of bacterial colonies using deep learning

Abstract

Counting bacterial colonies is a fundamental task in microbiology. Currently, manual counting remains the gold standard. This is a timeconsuming and error-prone process, which requires a trained professional. To avoid these issues, the automated method can be applied for the task. The goal of our work was to design a model that counts and classifies bacterial colonies in Petri dishes using RGB images.