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Use the method and system of the detection and classification for unit of convolutional neural networks

机译:使用卷积神经网络单元检测和分类的方法和系统

摘要

An artificial neural network system implemented on a computer for cell segmentation and classification of biological images. It includes a deep convolutional neural network as a feature extraction network, a first branch network connected to the feature extraction network to perform cell segmentation, and a second branch network connected to the feature extraction network to perform cell classification using the cell segmentation map generated by the first branch network. The feature extraction network is a modified VGG network where each convolutional layer uses multiple kernels of different sizes. The second branch network takes feature maps from two levels of the feature extraction network, and has multiple fully connected layers to independently process multiple cropped patches of the feature maps, the cropped patches being located at a centered and multiple shifted positions relative to the cell being classified; a voting method is used to determine the final cell classification.
机译:在计算机上实现的人工神经网络系统,用于细胞分割和生物图像分类。它包括作为特征提取网络的深度卷积神经网络,连接到特征提取网络以进行细胞分割的第一分支网络以及连接到特征提取网络以使用由生成的细胞分割图进行细胞分类的第二分支网络。第一个分支网络。特征提取网络是经过修改的VGG网络,其中每个卷积层都使用大小不同的多个内核。第二分支网络从特征提取网络的两个级别中获取特征图,并具有多个完全连接的层以独立处理特征图的多个裁剪后的小块,裁剪后的小块位于相对于单元的居中位置和多个偏移位置分类;投票方法用于确定最终的单元格分类。

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