Graph matching encompasses a class of computational problems aimed at identifying a correspondence between the vertex sets of two graphs so as to maximise structural similarity or alignment. Exact ...

In 2026, Facebook’s algorithm is prioritizing short-form video, with Reels emerging as the key driver of discovery and engagement. Creators who lean into this format can connect with audiences far ...

Instagram and TikTok have rolled out major algorithm changes in 2026 aimed at penalizing recycled, low-effort, and mass-produced AI content. Instagram’s new Originality Score and shift to an ...

Marketplaces are not clean laboratories. On any large platform, a change rolled out to one group of users ripples across the entire system, affecting sellers who never saw the test, buyers on the ...

Chemists have long faced a maddening problem. The number of possible useful molecules is so vast that even the ones already ...

Abstract: State of the art anatomical tree matching algorithms find correspondences between trees that contain topological differences. However there are still open problems that were not considered ...

Abstract: This paper presents 3D-LGSC, an extension of the Local Graph Structure Consensus (LGSC) algorithm for robust image matching by incorporating depth information. While the original LGSC ...

Background Joint analyses across multiple health datasets can increase statistical power and improve the generalisability of ...

Graph matching constitutes a fundamental class of techniques for establishing correspondences between structured entities in images, where keypoints or regions are represented as nodes and their ...

This research involving human participants complies with all relevant ethical regulations, including obtaining informed consent from all participants through the recruitment sites. Ethical review and ...