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A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

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关键词 Cellular electron cryo-tomography Macromolecular complex Subtomogram classification Visual proteomics Particle picking Structural pattern mining Deep learning Convolutional neural network Convolutional autoencoder Image semantic segmentation Machine learning Unsupervised learning Weakly supervised learning Pose normalization

发布时间 2018-10-30

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Journal of Structural Biology

2018年202卷2期

150-160页

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Journal of Structural Biology

2018年202卷2期

150-160页

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A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

Journal of Structural Biology

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同项目论文

Journal of Structural Biology

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A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

Journal of Structural Biology

相似文献

同项目论文

Journal of Structural Biology

相关期刊

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