基于迁移学习和支持向量机的白细胞分类

针对人工镜检分类白细胞准确率和效率低的问题,基于深度学习和机器学习算法,提出了一种基于迁移学习和支持向量机的白细胞分类方法.首先对迁移模型进行微调训练,其次用微调训练后的迁移模型进行特征提取,然后将特征输入至神经网络和支持向量机中进行训练,最后通过神经网络和支持向量机的组合分类器对白细胞进行分类.实验结果表明,白细胞分...

White Blood Cell Classification Based on Transfer Learning and SVM

Aiming at the low accuracy and efficiency of manual microscopic examination of white blood cell classification, based on deep learning and machine learning algorithms, a white blood cell classification method based on transfer learning and support vector machine is proposed. First, perform fine-tuning training on the transfer model, then use the fine-tuned training transfer model for feature extraction, then input the features into the neural network and support vector machine for training, and finally classify the white blood cells through the combined classifier of neural network and support vector machine. The experimental results show that the accuracy of white blood cell classification has increased from 83.26% of the initial fine-tuning training to 90.43% with the optimization of the transfer model, and finally increased to 93.52% through the combined classifier, which can help doctors improve the accuracy of diagnosis in clinical practice and efficiency.