Due to the inherent flexibility of prompting, foundation models have emerged as the
predominant force in the fields of natural language processing and computer vision. The …

Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise
information for diverse downstream applications. Recent development of the segment …

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …

Despite that the segment anything model (SAM) achieved impressive results on general-
purpose semantic segmentation with strong generalization ability on daily images, its …

Most recent scribble-supervised segmentation methods commonly adopt a CNN framework
with an encoder-decoder architecture. Despite its multiple benefits, this framework generally …

Self-supervised learning (SSL) is an efficient pre-training method for medical image
analysis. However current research is mostly confined to certain modalities consuming …

Automatically labeling and segmenting vertebrae in 3D CT images compose a complex
multi-task problem. Current methods progressively conduct vertebra labeling and semantic …

Recently, large language models such as ChatGPT have made huge strides in
understanding and generating human-like text and have demonstrated considerable …

Background Stroke is a leading cause of death and disability worldwide. Rapid and accurate
diagnosis is crucial for minimizing brain damage and optimizing treatment plans. Objective …

Accurately detecting tea bud leaves is crucial for the automation of tea picking robots.
However, challenges arise due to tea stem occlusion and overlapping of buds and leaves …