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CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study
Prostate cancer is the most common cancer among US men.
USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
The following mixed scheme is used for training/testing: (i) training on either each individual dataset or multiple prostate MRI datasets and (ii) testing on all three datasets with all possible training/testing combinations.
Analysing Features Learned Using Unsupervised Models on Program Embeddings
In this paper, we propose a novel approach for analyzing and evaluating how a deep neural network is autonomously learning different features related to programs on different input representations.
Mining Program Properties From Neural Networks Trained on Source Code Embeddings
In this paper, we propose a novel approach for mining different program features by analysing the internal behaviour of a deep neural network trained on source code.
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