Abstract
Convolutional neural networks have been frequently utilized in computer-aided diagnosis (CAD). Breast cancer image classification is one of the vital applications of CAD. The purpose of this study was to explore the role of attention mechanism in breast cancer image classification. Specifically, this study introduces attention mechanism into the classical image classification deep learning network and constructs a new breast cancer image classification model. Test results indicate that convolutional neural networks perform better in classification when an attention mechanism is added, and they also perform better in terms of training loss and accuracy.
Published Version
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