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Found 4 papers, 1 papers with code
COVID-19 Lung Lesion Segmentation Using a Sparsely Supervised Mask R-CNN on Chest X-rays Automatically Computed from Volumetric CTs
Chest X-rays of coronavirus disease 2019 (COVID-19) patients are frequently obtained to determine the extent of lung disease and are a valuable source of data for creating artificial intelligence models.
Piecewise convexity of artificial neural networks
Finally, that the network as a function of all its parameters is piecewise multi-convex, a generalization of biconvexity.
CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss
To achieve the best results from data augmentation, our model uses the intersection-over-union (IOU) loss function, a close relative of the Dice loss.
Probabilistic bounds on neuron death in deep rectifier networks
Neuron death is a complex phenomenon with implications for model trainability: the deeper the network, the lower the probability of finding a valid initialization.
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