PointCNN: convolution on Χ -transformed points

372 indexed citations
published 2018

Countries where authors are citing PointCNN: convolution on Χ -transformed points

Specialization
Citations

This map shows the geographic impact of PointCNN: convolution on Χ -transformed points. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by PointCNN: convolution on Χ -transformed points with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites PointCNN: convolution on Χ -transformed points more than expected).

Fields of papers citing PointCNN: convolution on Χ -transformed points

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of PointCNN: convolution on Χ -transformed points. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the PointCNN: convolution on Χ -transformed points.

About PointCNN: convolution on Χ -transformed points

This paper, published in 2018, received 372 indexed citations . Written by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di and Baoquan Chen covering the research area of Geology, Aerospace Engineering and Computational Mechanics. It is primarily cited by scholars working on Computational Mechanics (249 citations), Geology (201 citations) and Computer Vision and Pattern Recognition (169 citations).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w57373836.

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