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Found 3 papers, 3 papers with code
A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images
Diffusion models are a special type of generative model, capable of synthesising new data from a learnt distribution.
Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction
We propose to complement geometrical shape information by including multi-scale topological features, such as connected components, cycles, and voids, in the reconstruction loss.
InstantDL-An easy-to-use deep learning pipeline for image segmentation and classification
InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort.
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