detalle del documento
IDENTIFICACIÓN
oai:arXiv.org:2404.09226
Tema
Electrical Engineering and Systems... Computer Science - Computer Vision... Computer Science - Machine Learnin...Autor
Wang, Weimin Li, Yufeng Yan, Xu Xiao, Mingxuan Gao, MinCategoría
Computer Science
Año
2024
fecha de cotización
18/9/2024
Palabras clave
science transfer deep algorithm computer imageResumen
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 efficiency of over 84.0\% in the test set, with a significantly improved classification accuracy compared to previous models, making it applicable to medical breast cancer detection tasks.
;Comment: 12 pages, 8 figures, 2024 International Conference on Image Processing, Machine Learning and Pattern Recognition
Wang, Weimin,Li, Yufeng,Yan, Xu,Xiao, Mingxuan,Gao, Min, 2024, Breast Cancer Image Classification Method Based on Deep Transfer Learning
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