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Found 3 papers, 2 papers with code
Enhancing Boundary Segmentation for Topological Accuracy with Skeleton-based Methods
Topological consistency plays a crucial role in the task of boundary segmentation for reticular images, such as cell membrane segmentation in neuron electron microscopic images, grain boundary segmentation in material microscopic images and road segmentation in aerial images.
WPU-Net: Boundary Learning by Using Weighted Propagation in Convolution Network
In this work, we propose WPU-net that redesigns the architecture and weighted loss of U-Net, which forces the network to integrate information from adjacent slices and pays more attention to the topology in boundary detection task.
Data augmentation in microscopic images for material data mining
Recent progress in material data mining has been driven by high-capacity models trained on large datasets.
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