Bacterial Classification in Microbiology using BiT

Bacteria are microscopic living organisms which have only one cell in it and they are classified into many different types. Microbial classification holds a crucial role in shaping our understanding of the microscopic realm, impacting scientific exploration, medical practices, environmental sciences, and various industrial applications. In the medical field, microbial classification is indispensable for disease diagnosis, treatment, and prevention. In the industrial sector, microbial classification is fundamental for bioprocessing, biofuel production, and bioremediation. Understanding microbial characteristics enables industries to harness their capabilities for efficient production and environmental remediation. It plays very important role in both environment and human life however some other kinds of bacteria are considered as very harmful. Harmful bacteria can cause serious diseases and illness. So it’s very important to classify bacteria for proper diagnosis. Given the vast diversity of microorganisms and difference in appearance, manually classifying bacteria is a challenging task which takes lot of time. So,This paper aims to streamline this arduous task by employing deep learning techniques such as using ResNet50 architecture and using BiT. The integration of BiT and ResNet at different stages ensures efficient feature extraction and classification, leading to high accuracy and reliability in bacterial classification tasks.