Pattern Analysis and Applications

1.5k papers and 18.8k indexed citations i.

About

The 1.5k papers published in Pattern Analysis and Applications in the last decades have received a total of 18.8k indexed citations. Papers published in Pattern Analysis and Applications usually cover Computer Vision and Pattern Recognition (998 papers), Artificial Intelligence (581 papers) and Signal Processing (216 papers) specifically the topics of Face and Expression Recognition (237 papers), Image Retrieval and Classification Techniques (227 papers) and Advanced Image and Video Retrieval Techniques (195 papers). The most active scholars publishing in Pattern Analysis and Applications are Ziynet Pamuk, Ceren Kaya, Ali Narin, Robert P. W. Duin, Josef Kittler, Marina Skurichina, Adnan Amin, Neil Yager, Li Bai and Tin Kam Ho.

In The Last Decade

Fields of papers published in Pattern Analysis and Applications

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Pattern Analysis 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 Pattern Analysis and Applications.

Countries where authors publish in Pattern Analysis and Applications

Since Specialization
Citations

This map shows the geographic impact of research published in Pattern Analysis 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 Pattern Analysis 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 Pattern Analysis 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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