Breast Cancer Image Classification Method Based on Deep Transfer Learning

arXiv:2404.09226v1 Announce Type: cross
Abstract: To address the issues of limited samples, time-consuming feature design, and low accuracy in detection and classification of breast cancer pathological images, a breast cancer image classification model algorithm combining deep learning and transfer learning is proposed. This algorithm is based on the DenseNet structure of deep neural networks, and constructs a network model by introducing attention mechanisms, and trains the enhanced dataset using multi-level transfer learning. Experimental results demonstrate that the algorithm achieves an …

abstract accuracy algorithm arxiv cancer classification classification model cs.cv cs.lg deep learning design detection eess.iv feature image images low samples transfer transfer learning type