现代信息科技2024，Vol.8Issue(7)：86-90,5.DOI:10.19850/j.cnki.2096-4706.2024.07.019
基于CNN与迁移学习实现肺部影像分类识别
Classification and Recognition of Lung Image Based on CNN and Transfer Learning
摘要
Abstract
This paper presents an innovative research on intelligent classification and recognition of lung images based on Deep Learning methods,and proposes a method based on Convolutional Neural Networks(CNN)and Transfer Learning,which uses classic CNN models such as VGG,InceptionV3 and ResNet as pre-trained models,and selects different Transfer Learning strategies according to the size and similarity of the datasets.This paper also uses techniques such as data augmentation,batch normalization and regularization to improve the generalization ability and stability of the model.We conduct experiments on two public lung image datasets of COVID-19 CT scans and LIDC-IDRI.The experimental results demonstrate the effectiveness and robustness of the proposed method,which can help improve the diagnostic efficiency and accuracy.关键词
卷积神经网络/迁移学习/肺部疾病Key words
Convolutional Neural Networks/Transfer Learning/lung disease分类
信息技术与安全科学引用本文复制引用
刘艺峰,罗亮..基于CNN与迁移学习实现肺部影像分类识别[J].现代信息科技,2024,8(7):86-90,5.基金项目
全国大学生创业训练计划目(202210554001X) （202210554001X）
