Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation 截至3.8,引用次数22 这篇文章把CT腹部扫描图分割当成一个分类问题处理,使用一个基于CNN的级连分类器框架。使用两个编码解码器卷积网络训练来进行级联分割肝和病灶(EDCNN)。即第一个EDCNN分割肝图片的结果(ROI区域)作...
The convolutional layers are pre-trained as part of an MNIST digit classifier and adapted for use in the encoder-decoder network, before the network is trained using a dataset composed of digit images and corresponding writing trajectories. This architecture was tested on several challenging noisy ...
CSDN 同名账号同步发表一、架构标题放不下了,论文全称:Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections 其实就是conv和deconv,外加对称的skip con…
Siam LawawirojwongGeo-Informatics and Space Technology Development Agency (Public Organization)Springer, ChamInternational Conference on Computing and Information Technologyanboonyuen, T.; Vateekul, P.; Jitkajornwanich, K.; awawirojwong, S. An Enhanced Deep Convolutional Encoder-Decoder Network for ...
In this paper, we propose a convolutional neural network, which is based on down sampling followed by up sampling architecture for the purpose of road extraction from aerial images. Our model consists of convolutional layers only. The proposed encoder-decoder structure allows our network to retain ...
This is essentially a Convolutional Encoder Decoder network based on the SegNet architecture for unsupervised feature learning. The particular network can be used for unsupervised feature learning on particular datasets, as well as then fine-tune (further train) the pre-trained network for semantic seg...
The multifidelity network is able to correctly leverage the Conclusions and future work In this work, we focus on convolutional neural networks, specifically architectures resulting from an assembly of encoders, decoders and skip connections. Such architectures have the flexibility to predict the result...
encoder网络:其结构与VGG16网络的前13层卷积层的结构相似。decoder网络:作用是将由encoder的到的低分辨率的feature maps 进行映射得到与输入图像featuremap相同的分辨率进而进行像素级别的分类。Segnet的亮点:decoder进行上采样的方式,直接利用与之对应的encoder阶段中进行max-pooling时的polling index 进行非线性上采样,这样...
具体来讲,Stacked What-Where Auto-encoders(SWWAE)基于前向 Convnet 和前向 Deconvnet,并将 max-pooling 的输出称为 “what”,其实就是将maxfunction 的 content 和 position 传给下一层;同时,max-pooling 中的 position/location 信息,也就是argmaxfunction,作为 “where” 要“横向”传给 decoder。这样,...
In the testing step, for a new given test patient, the MRI goes through the trained network to obtain the corresponding sCT. In sCT generation from MRI, the generator architectures are generally based on convolution encoder-decoder networks (CED). In the literature, the variants of generator ...