Lecture notes in computer science

18.0k papers and 239.3k indexed citations i.

About

The 18.0k papers published in Lecture notes in computer science in the last decades have received a total of 239.3k indexed citations. Papers published in Lecture notes in computer science usually cover Artificial Intelligence (3.2k papers), Computer Vision and Pattern Recognition (2.9k papers) and Radiology, Nuclear Medicine and Imaging (1.9k papers) specifically the topics of Medical Image Segmentation Techniques (1.4k papers), Advanced Neuroimaging Techniques and Applications (675 papers) and Advanced MRI Techniques and Applications (616 papers). The most active scholars publishing in Lecture notes in computer science are R. Milner, Dinggang Shen, Rory Stark, Jianming Liang, Nima Tajbakhsh, Nassir Navab, Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Klaus‐Robert Müller and Gerhard Goos.

In The Last Decade

Fields of papers published in Lecture notes in computer science

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Lecture notes in computer science. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Lecture notes in computer science.

Countries where authors publish in Lecture notes in computer science

Since Specialization
Citations

This map shows the geographic impact of research published in Lecture notes in computer science. 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 papers published in Lecture notes in computer science with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lecture notes in computer science more than expected).

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.

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