Search Results for author:
Found 2 papers, 1 papers with code
BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision
Brain stroke has become a significant burden on global health and thus we need remedies and prevention strategies to overcome this challenge.
Ranked #1 on
Acute Stroke Lesion Segmentation
on ATLAS v2.0
fMRI Semantic Category Decoding using Linguistic Encoding of Word Embeddings
Unlike the models with hand-crafted features that have been used in the literature, in this paper we propose a novel approach wherein decoding models are built with features extracted from popular linguistic encodings of Word2Vec, GloVe, Meta-Embeddings in conjunction with the empirical fMRI data associated with viewing several dozen concrete nouns.
