Ensemble CNNs for Breast Tumor Classification

The other key challenge in To improve the recognition ability of computer-aided breast mass mammographic image analysis is difference between classification among mammographic images, in this work we mammographic images and RGB images, that makes it difficult to explore the state-of-the-art classification networks to develop an apply classification models with good performance on RGB images ensemble mechanism. First, the regions of interests (ROIs) are to mammographic images. In breasts, masses are typically isodense obtained from the original dataset and then three models, i.e., or dense, thus it has the characteristics of pixel intensity from gray XceptionNet, DenseNet, and EfficientNet, are trained individually.