Accurate and fast segmentation of medical images is clinically essential...
Existing studies tend tofocus onmodel modifications and integration with...
Image segmentation is an important task in the medical image field and m...
Spatial-temporal local binary pattern (STLBP) has been widely used in dy...
Purpose: To develop a scan-specific model that estimates and corrects k-...
As a sequence-to-sequence generation task, neural machine translation (N...
Recent studies have demonstrated the overwhelming advantage of cross-lin...
Recent evidence reveals that Neural Machine Translation (NMT) models wit...
Compared with only using limited authentic parallel data as training cor...
Transformer, based on the encoder-decoder framework, has achieved
state-...
Pre-training and fine-tuning have achieved great success in the natural
...
Monolingual data has been demonstrated to be helpful in improving the
tr...
The encoder-decoder framework has achieved promising process for many
se...
Leveraging user-provided translation to constrain NMT has practical
sign...
Measuring the semantic similarity between two sentences (or Semantic Tex...
We introduce an agreement-based approach to learning parallel lexicons a...