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Found 4 papers, 1 papers with code
Cluster-Based Autoencoders for Volumetric Point Clouds
Autoencoders allow to reconstruct a given input from a small set of parameters.
A Joint Deep Learning Approach for Automated Liver and Tumor Segmentation
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer in adults, and the most common cause of death of people suffering from cirrhosis.
NETT: Solving Inverse Problems with Deep Neural Networks
Our theoretical results and framework are different from any previous work using neural networks for solving inverse problems.
Deep Learning for Photoacoustic Tomography from Sparse Data
In our approach image reconstruction is performed with a deep convolutional neural network (CNN), whose weights are adjusted prior to the actual image reconstruction based on a set of training data.
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