Optical Memory and Neural Networks

538 papers and 1.9k indexed citations i.

About

The 538 papers published in Optical Memory and Neural Networks in the last decades have received a total of 1.9k indexed citations. Papers published in Optical Memory and Neural Networks usually cover Electrical and Electronic Engineering (145 papers), Atomic and Molecular Physics, and Optics (129 papers) and Artificial Intelligence (119 papers) specifically the topics of Neural Networks and Applications (72 papers), Photonic and Optical Devices (58 papers) and Orbital Angular Momentum in Optics (38 papers). The most active scholars publishing in Optical Memory and Neural Networks are Svetlana N. Khonina, A. Savchenko, С. А. Субботин, Nikolay L. Kazanskiy, С. В. Карпеев, В В Давыдов, V. I. Dudkin, Boris Kryzhanovsky, Vladimir Golovko and A. Yu. Karseev.

In The Last Decade

Fields of papers published in Optical Memory and Neural Networks

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Optical Memory and Neural Networks. 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 Optical Memory and Neural Networks.

Countries where authors publish in Optical Memory and Neural Networks

Since Specialization
Citations

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