深层析成像专利的初步景观分析。

4区计算机科学 Q1 Arts and Humanities

Visual Computing for Industry, Biomedicine, and Art Pub Date : 2023-01-23 DOI:10.1186/s42492-023-00130-x

Qingsong Yang, Donna L Lizotte, Wenxiang Cong, Ge Wang

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引用次数: 0

摘要

近年来，专利文献的重要性已越来越多地认识到在学术设置。在人工智能、深度学习和数据科学的背景下，专利不仅与行业相关，而且与学术界和其他社区相关。在这篇文章中，我们聚焦于深层层析成像，并对相关的专利文献进行了初步的景观分析。我们的搜索工具是PatSeer。我们的专利文献计量数据汇总在各种图表中。特别是，我们定性地分析了关键的深层层析专利文献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Preliminary landscape analysis of deep tomographic imaging patents.

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Preliminary landscape analysis of deep tomographic imaging patents.

Over recent years, the importance of the patent literature has become increasingly more recognized in the academic setting. In the context of artificial intelligence, deep learning, and data sciences, patents are relevant to not only industry but also academe and other communities. In this article, we focus on deep tomographic imaging and perform a preliminary landscape analysis of the related patent literature. Our search tool is PatSeer. Our patent bibliometric data is summarized in various figures and tables. In particular, we qualitatively analyze key deep tomographic patent literature.

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来源期刊

Visual Computing for Industry, Biomedicine, and Art Arts and Humanities-Visual Arts and Performing Arts

CiteScore

5.60

自引率

0.00%

发文量

审稿时长

5 weeks