Although convolutional neural networks (CNNs) have shown good performance on grid data, they are limited in the semantic segmentation of irregular point clouds. This article proposes a novel and ...

Describe the new feature If you have a busy graph and want to just look at the results of one series, it's almost impossible to hide everything. Recommend adding a select all and select none button to ...

Methods: This paper introduces a Multi-Frequency EEG data-based Multi-Graph Convolutional Network (MF-MGCN) model for AD diagnosis. This method integrates both functional and structural connectivity ...

Abstract The cost and strict input format requirements of GraphRAG make it less efficient for processing large documents. This paper proposes an alternative approach for constructing a knowledge graph ...

In oilfield surface gathering and transportation systems, precise control of water injection is crucial for stabilizing wellhead pressure, ensuring efficient system operation, and conserving resources ...

A team of researchers from Southeast University, Beijing Institute of Mathematical Sciences, Yale, and UC San Diego introduced GraphIC, a graph-based ICE retrieval method. GraphIC uses graph ...

We are at a critical time and supporting climate journalism is more important than ever. Science News and our parent organization, the Society for Science, need your help to strengthen ...

Key point correspondence plays an important role in lunar surface image processing. Since lunar surface images often contain obvious illumination changes, noisy points and repetitive patterns, ...

[TPAMI] GROR:A New Outlier Removal Strategy Based on Reliability of Correspondence Graph for Fast Point Cloud Registration - WPC-WHU/GROR ...

In contrast, our method does not require any training as it uses botanical knowledge within the algorithm. As a consequence, it can handle point clouds with hundreds of thousands of points directly ...