Detection and Classification of Colorectal Cancer Types

Using Deep Residual Learning based on ResNet-50 with Adam Optimization Method

This research explores deep learning methods using ResNet architectures and optimization methods for colorectal cancer classification. The ResNet-50 model with Adam optimization achieved 99.86% accuracy, outperforming other methods and proving effective in colon tumor segmentation.