Convolutional Neural Network - CS256-FC256

Convolutional Neural Network (CNN) trained for patch-based classification of invasive breast cancer from histopathology digital images. The CNN architecture is 256 units in convolution and pooling layers, 256 units of fully connected layer and 2 units for output classification layer of softmax. The model was trained with Torch7.卷积神经网络（Convolutional Neural Network，CNN）被训练用于从组织病理学数字图像中完成侵袭性乳腺癌的图像块级分类任务。该CNN的网络架构为：卷积与池化层包含256个神经元单元，全连接层包含256个神经元单元，输出分类层采用Softmax激活函数，共设置2个输出单元。该模型基于Torch7框架完成训练。