Neural Computing and Applications

10.2k papers and 183.1k indexed citations i.

About

The 10.2k papers published in Neural Computing and Applications in the last decades have received a total of 183.1k indexed citations. Papers published in Neural Computing and Applications usually cover Artificial Intelligence (4.0k papers), Computer Vision and Pattern Recognition (2.5k papers) and Control and Systems Engineering (1.4k papers) specifically the topics of Neural Networks and Applications (1.1k papers), Metaheuristic Optimization Algorithms Research (583 papers) and Face and Expression Recognition (550 papers). The most active scholars publishing in Neural Computing and Applications are Seyedali Mirjalili, Seyed Mohammad Mirjalili, Laith Abualigah, Abdolreza Hatamlou, Xin‐She Yang, Amir H. Gandomi, Shiliang Sun, Panagiotis G. Asteris, Suash Deb and Ahmad Taher Azar.

In The Last Decade

Fields of papers published in Neural Computing and Applications

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Neural Computing and Applications. 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 Neural Computing and Applications.

Countries where authors publish in Neural Computing and Applications

Since Specialization
Citations

This map shows the geographic impact of research published in Neural Computing and Applications. 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 Neural Computing and Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neural Computing and Applications 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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