论文标题
细胞图像分割的反馈注意
Feedback Attention for Cell Image Segmentation
论文作者
论文摘要
在本文中，我们通过反馈处理机制（例如反馈处理）来解决单元格的分割任务。与传统的进食处理过程不同，我们专注于人脑中的反馈处理，并假设网络通过将特征图从深层连接到浅层层来学习人类。我们提出了一些模仿人大脑的反馈注意事项，并将输出层的特征图馈回输入。与反馈注意的U-NET相比仅使用FeedForward处理的常规方法显示出更好的结果。
In this paper, we address cell image segmentation task by Feedback Attention mechanism like feedback processing. Unlike conventional neural network models of feedforward processing, we focused on the feedback processing in human brain and assumed that the network learns like a human by connecting feature maps from deep layers to shallow layers. We propose some Feedback Attentions which imitate human brain and feeds back the feature maps of output layer to close layer to the input. U-Net with Feedback Attention showed better result than the conventional methods using only feedforward processing.
