Search Results for author:
Found 3 papers, 0 papers with code
ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision
The recent advances in representation learning inspire us to take on the challenging problem of unsupervised image classification tasks in a principled way.
Shuffle & Divide: Contrastive Learning for Long Text
We propose a self-supervised learning method for long text documents based on contrastive learning.
Finding essential parts of the brain in rs-fMRI can improve diagnosing ADHD by Deep Learning
As a result, when we only used 15 important region of interest(ROIs) for training, an accuracy of 70. 6% was obtained, significantly exceeding the existing results of 68. 6% from all ROIs.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
