Breast Cancer Identification Study Using Improved VGG

被引：2
作者：
Li, Yanzhang [1 ]
Deng, Kaiqi [1 ]
机构：
[1] Hainan Univ, Dept Elect Sci & Technol, Haikou, Hainan, Peoples R China
来源：
2023 8TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYTICS, ICCCBDA | 2023年
关键词：
breast cancer; classification; VGG convolutional neural network; attentional mechanisms;
D O I：
10.1109/ICCCBDA56900.2023.10154755
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A classification recognition algorithm based on improved VGG16 for breast cancer histopathology images is proposed to deal with the problem of binary recognition of breast cancer pathology images. Because some pathological images are very similar to each other, which leads to the problem of false detection. Therefore, attention mechanism is applied to increase the weight of effective feature map to make the training model get better effect and improve the accuracy of the algorithm. Verified by comparative experiment, the convergence speed and accuracy of the improved VGG16 model are higher than those of the original DenseNet and VGG16 models, reaching 98.41% of the recognition accuracy.
引用
收藏
页码：467 / 470
页数：4
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