手机蟹苗计数
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Automated Counting of Bacterial Colony Forming Units on Agar Plates
Abstract Manual counting of bacterial colony-forming units (CFUs) on agar plates is laborious and error-prone. Therefore, we implemented a colony counting system with a new segmentation algorithm to distinguish bacterial colonies from agar plates. So as to achieve the purpose of counting the number of colonies. We designed a colony counter software called "CountThings By Camera", which you can find in the app store. Use a deep learning framework to build a deep learning neural network. Through long-term training on a large number of colony samples, we obtained a relatively accurate The model can also perform well in the case of colony adhesion. To evaluate the accuracy and performance of the colony counter, we tested the colony counts under different densities, colors, and backgrounds. The results are very satisfactory, and in most cases, the software can perform the counting task well. Less In some cases, there will be a small number of errors. It can be corrected through