KAIST’s Upsample Anything tackles the memory problem behind sharper on-device AI vision, restoring high-resolution visual features from compressed image data without forcing smartphones to process ...
Abstract: Medical image segmentation serves as a fundamental prerequisite for clinical diagnosis and treatment planning. Despite their remarkable success, existing methods often disproportionately ...
Abstract: The level set model (LSM) is a classical approach for image segmentation. While global region-based LSMs struggle with intensity inhomogeneity, local region-based methods, though effective ...
Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT data). In ...
After receiving his degree in Journalism & Media Communications from CSU in 2019, Erik began building his career in online media, and found his dream job when he joined Game Rant as a staff writer.
1 School of Science, Tianjin University of Technology and Education, Tianjin, China. 2 School of Big Data, Lvliang Vocational and Technical College, Lvliang, China. Early image segmentation was mainly ...
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 ...
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