关键词: 卷积神经网络, 单细胞, 特征提取, 细胞图像分类

Abstract: In this paper, aiming at the problem of classical convolutional neural network can not be used for single cell image classification effectively, Faraki M and Nosaka R’s methods need complex feature extraction and incomplete image is not considered. A new method of single cell image classification based on the same level multi scale kernel convolution neural network is proposed, based on the classical convolutional neural network model LeNet-5. Using the ICPR2012 HEp-2 data set of computer simulation experiments, the simulation results show that the correct rate of classification in the same layer of multiscale convolution neural network model has higher, better robustness, single cell map for rotation, incomplete contrast and brightness changes can still classify.

Key words: convolution neural network, single cell, feature extraction, cell image classification