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Found 4 papers, 1 papers with code
DenseUNets with feedback non-local attention for the segmentation of specular microscopy images of the corneal endothelium with guttae
To estimate the corneal endothelial parameters from specular microscopy images depicting cornea guttata (Fuchs dystrophy), we propose a new deep learning methodology that includes a novel attention mechanism named feedback non-local attention (fNLA).
Rotaflip: A New CNN Layer for Regularization and Rotational Invariance in Medical Images
Regularization in convolutional neural networks (CNNs) is usually addressed with dropout layers.
Redesigning Fully Convolutional DenseUNets for Large Histopathology Images
The automated segmentation of cancer tissue in histopathology images can help clinicians to detect, diagnose, and analyze such disease.
Parallel Capsule Networks for Classification of White Blood Cells
We applied our concept to the two current types of CapsNet architectures, studying the performance for networks with different layers of capsules.
