A5111797937- Advanced Clustering Algorithms Research
- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
- Adipose Tissue and Metabolism
- Advanced Data Compression Techniques
- Machine Learning in Bioinformatics
- Complex Network Analysis Techniques
- Biochemical Analysis and Sensing Techniques
- Image Retrieval and Classification Techniques
- Data Stream Mining Techniques
- Genomics and Phylogenetic Studies
- Regulation of Appetite and Obesity
- Data Management and Algorithms
- Peer-to-Peer Network Technologies
- Generative Adversarial Networks and Image Synthesis
- Glycosylation and Glycoproteins Research
Peking University
2024
University of Copenhagen
2014
China Telecom
2011
China Telecom (China)
2011
Nanjing University of Science and Technology
2008
Northwest A&F University
2005
Medical image segmentation is a critical task in clinical applications. Recently, the Segment Anything Model (SAM) has demonstrated potential for natural segmentation. However, requirement expert labour to provide prompts, and domain gap between medical images pose significant obstacles adapting SAM images. To overcome these challenges, this paper introduces novel prompt generation method named EviPrompt. The proposed requires only single reference image-annotation pair, making it...
Abstract Background The inference of homology from statistically significant sequence similarity is a central issue in alignments. So far the statistical distribution function underlying optimal global alignments has not been completely determined. Results In this study, random and real but unrelated sequences prepared six different ways were selected as reference datasets to obtain their respective distributions alignment scores. All carried out with Needleman-Wunsch algorithm scores fitted...