A Review of Various Deep Learning Models for Mammogram Enhancement and Breast Cancer Detection

In order to improve mammography images and identification of breast cancer, this research provides a thorough comparison analysis of several deep learning models. In addition to other models like CNN with Transfer Learning, EfficientNet, ResNet-50, DenseNet-169, VGG-16, YOLO Detector, and Hybrid CNN. These are the pre-trained network learning models which are trained over millions of images to perform the similar batch work. The performance of each model is evaluated using its accuracy, area under the curve (AUC), and other pertinent metrics, showing notable advancements in the use of deep learning in medical imaging for the early identification of breast cancer.