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Semi-supervised Deep Learning for Fully Convolutional Networks
[chapter]
2017
Lecture Notes in Computer Science
Deep learning usually requires large amounts of labeled training data, but annotating data is costly and tedious. The framework of semi-supervised learning provides the means to use both labeled data and arbitrary amounts of unlabeled data for training. Recently, semisupervised deep learning has been intensively studied for standard CNN architectures. However, Fully Convolutional Networks (FCNs) set the state-of-the-art for many image segmentation tasks. To the best of our knowledge, there is
doi:10.1007/978-3-319-66179-7_36
fatcat:tgqldjfnhzhn5akjlmoxbgegim