1 citations · 1 across the 3 of their papers we have counts for
3 papers
Evaluating unsupervised contrastive learning framework for MRI sequences classification
Yuli Wang, Kritika Iyer, Sep Farhand +1
The automatic identification of Magnetic Resonance Imaging (MRI) sequences can streamline clinical workflows by reducing the time radiologists spend manually sorting and identifyin…
Dual-Domain Cross-Iteration Squeeze-Excitation Network for Sparse Reconstruction of Brain MRI
Xiongchao Chen, Yoshihisa Shinagawa, Zhigang Peng +1
Magnetic resonance imaging (MRI) is one of the most commonly applied tests in neurology and neurosurgery. However, the utility of MRI is largely limited by its long acquisition tim…
Supervised Understanding of Word Embeddings
Halid Ziya Yerebakan, Parmeet Bhatia, Yoshihisa Shinagawa
Pre-trained word embeddings are widely used for transfer learning in natural language processing. The embeddings are continuous and distributed representations of the words that pr…