Colon also named large bowel and large intestine is the lowest part of human gastrointestinal tract. It is the third most common cancer in the world, and its rate of reported cases are continuously increasing. Colonoscopy is now the golden standard for detecting and removing the precancerous polyps. Manually endoscopy data analysis needs a lot of concentration and can be inaccurate at times. In this research work, an efficient Xception (E-Xception) model is trained for the detection of endoscopy absurdities in various areas of colon. We freeze the weights and biases of the model to use in our own model. In early detection of CRC, the fine-tune configuration has obtained 99.46% accuracy.
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