Recently, a research team developed an unsupervised domain adaptation (UDA) approach, the dual domain distribution disruption with semantics preservation (DDSP) framework, achieving high-precision ...
Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...
A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
Nuclei segmentation in histology images is an import step for identifying cells and doing analysis for problems such as disease identification and/or progression. In this effort, we focus on the lack ...
Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results