Fine-tuning large pretrained language models on a limited training corpus usually suffers
from poor generalization. Prior works show that the recently-proposed sharpness-aware …

Deep learning (DL) has shown remarkable success in various medical imaging data
analysis applications. However, it remains challenging for DL models to achieve good …

Accurate segmentation of brain tumors from medical images is important for diagnosis and
treatment planning, and it often requires multi-modal or contrast-enhanced images …

Image matching involves identifying the template region in the search image after selecting it
in the template image. Image matching, as a basic task, is a pre-order step of many image …

This open access book focuses on the field of aerospace propulsion theory and
engineering. The book takes the solar thermal thruster as the research object, has carried on …

Unsupervised domain adaptation (UDA) has recently garnered widespread attention in the
field of medical image segmentation by transferring knowledge from labeled source datasets …

Medical image segmentation has broad application prospects in the field of medical image
processing, providing auxiliary information for diagnosis and treatment by locating and …