Microbial-Recognition, Data Analytics
InceptionV3
Deep Learning
CNN
Machine Learning
Data Analytics
Built a deep-learning–based microorganism classification system using InceptionV3, automating the identification of bacteria and protozoa with high accuracy and reducing reliance on slow, manual laboratory methods. Executed a complete data analytics pipeline including image preprocessing, augmentation, model training/testing, and performance evaluation, while comparing traditional ML algorithms with modern CNN architectures. Provided critical insights into limitations, challenges, and future scope of AI-driven microbe classification, offering a scalable framework for researchers and industry applications.