[TMI2019-05]HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation

时间 2020-12-29

标签多模分割 TMI 繁體版

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HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation 最近，密集的连接吸引了计算机视觉的广泛关注，因为它们促进了训练过程中的梯度流和隐式的深度监控。尤其是，DenseNet 以前馈的方式将每一层连接到其他每一层，并在自然图像分类任务中显示出令人印象深刻的性能。我们提出了 HyperDense

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1. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
2. 【SegNet】 A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
3. Attention Guided Network for Retinal Image Segmentation
4. Context-Aware U-Net for Biomedical Image Segmentation
5. Weakly-supervised convolutional neural networks for multimodal image registration
6. 《UNet++: A Nested U-Net Architecture for Medical Image Segmentation》论文翻译
7. Multimodal——Paper简读笔记：Multimodal Image-to-Image Translation via a Single Generative Adversarial Net
8. Multimodal Unsupervised Image-to-Image Translation
9. TensorMask: A Foundation for Dense Object Segmentation
10. 【论文阅读】semantic image segmentation with deep convolutional nets and fully connected CRFs

>>更多相关文章<<