Graph neural networks excel at modeling pairwise interactions, but they cannot flexibly
accommodate higher-order interactions and features. Topological deep learning (TDL) has …

Abstract Three-dimensional (3D) scanning technologies could transform medical practices
by creating virtual tissue banks. In bone transplantation, new approaches are needed to …

Within the carcinogenesis mechanism, from the initiation of the very first tumor cell to the
preneoplastic and neoplastic cancer cell groups, cancer cells omnidirectionally and …

Size-invariant shape transformation is a technique of changing the shape of a domain while
preserving its sizes under the Lebesgue measure. In quantum-confined systems, this …

Monitoring and tracking the size and the number of multiple sclerosis (MS) lesions is very
important in clinical medicine to understand the course and estimate the progression of this …

Mobile applications (apps) are integral to our daily lives, offering diverse services and
functionalities. They enable sighted users to access information coherently in an extremely …

Magnetic resonance imaging (MRI) technology is rapidly advancing and three-dimensional
(3D) scanners started to play an important role on diagnosis. However, not every medical …

In hierarchical reinforcement learning, unsupervised skill discovery holds promise for
overcoming the challenge of sparse rewards commonly encountered in traditional …

The detection, localization, and interpretation of defects in textured surfaces pose
challenges for automatic visual inspection. Both fully-supervised and weakly-supervised …

In recent years, transformer-based paradigms have made substantial inroads in the domain
of CT image segmentation, The Swin Transformer has garnered praise for its strong …