Authors will have the option to choose how their article is published.

Traditional publishing model: published articles are made available to institutions and individuals who subscribe to this journal or who pay to read specific articles. There is no charge to publish.

Open Access (OA) model: published articles are freely and permanently available online. Anyone, anywhere can read and build upon this research. If you would be interested in publishing Open Access in this journal please follow the link.

USAGE

• 31640Downloads 2023
  Springer measures the usage on the SpringerLink platform according to the COUNTER (Counting Online Usage of NeTworked Electronic Resources) standards.
• 60.5 Usage Factor 2022/2023
  The Springer Journal Usage Factor 2022/2023 was calculated as suggested by the COUNTER Code of Practice for Usage Factors. It is the median value of the number of downloads in 2022/2023 for all articles published online in that particular journal during the same time period. The Usage Factor calculation is based on COUNTER-compliant usage data on the SpringerLink platform. (Counting Online Usage of NeTworked Electronic Resources) standards.

WEB OF SCIENCE

• 0.7 Impact Factor 2023
  The journal Impact Factor is the average number of times articles from the journal published in the past two years have been cited in the JCR year. It is calculated by dividing the number of citations in the JCR year by the total number of articles published in the two previous years.
• Q4Quartile: Computer Science, Interdisciplinary Applications 2023
  Quartiles indicate where a journal’s ranking lies within a particular subject category. These quartiles rank the journals from highest to lowest based on their impact factor. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.
• 0.16 Journal Citation Indicator (Computer Science, Interdisciplinary Applications) 2023
  The Journal Citation Indicator is a measure of the average Category Normalized Citation Impact (CNCI) of citable items (articles & reviews) published by a journal over a recent three year period. It is used to help you evaluate journals based on other metrics besides the Journal Impact Factor (JIF).

SCOPUS

• 1.8 CiteScore 2023
  CiteScore acts as an indicator of the citation level of peer-reviewed materials, which is calculated as the ratio of the average number of citations to the number of published documents. Therewith, the publication window is equal to four years.
• 0.58Source Normalized Impact per Paper (SNIP) 2023
  Source Normalized Impact per Paper (SNIP) measures contextual citation impact by weighting citations based on the total number of citations in a subject field. The impact of a single citation is given higher value in subject areas where citations are less likely, and vice versa.
• 0.362 SCImago Journal Rank (SJR) 2023
  SCImago Journal Rank (SJR) is a measure of scientific influence of scholarly journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from.
• Q3Quartile: Computer Vision and Pattern Recognition 2023
  Quartiles indicate where a journal’s ranking lies within a particular subject category. These quartiles rank the journals from highest to lowest based on their SJR. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.
• 33H-Index 2023
  A journal has an H index of h if it published h papers each of which has been cited in other journals at least h times. Calculations are based on Scopus.

Pattern Recognition and Image Analysis  is a peer-reviewed journal that publishes the results of fundamental and applied scientific research in the fields of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. The journal makes it possible to rapidly publish original research articles and critical reviews. It features articles written by the world's leading scientists and solicited by the editorial board. Some of the journal issues are devoted to specific themes or proceedings of international conferences and workshops. The journal is one of the top ten global periodicals on image analysis and pattern recognition and is the only publication on this topic in Central and Eastern Europe. The journal is an international publication and publishes manuscripts originally submitted in English from all countries along with translated works.

1) scientists, specialists, teachers of general education and technical universities, engineers, developers of information technologies and software and algorithmic complexes and systems, postgraduates and undergraduates specializing in:

a) image analysis and pattern recognition;
b) computer science and applied mathematics.

2) scientists, specialists, teachers of general education and technical universities, engineers, developers of information technologies and software and algorithmic complexes and systems, postgraduates and undergraduates of various specialties who are faced with the tasks of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including applied problems of image recognition and analysis.

ACM Digital Library, Baidu, CLOCKSS, CNKI, CNPIEC, Dimensions, EBSCO, EI Compendex, Emerging Sources Citation Index, Google Scholar, INSPEC, Japanese Science and Technology Agency (JST), Naver, OCLC WorldCat Discovery Service, Portico, ProQuest, Russian Science Citation Index, SCImago, SCOPUS, TD Net Discovery Service, UGC-CARE List (India), Wanfang

Queries about submission issues, peer review process, or the status of your manuscript should be sent to the Editorial Office of Pattern Recognition and Image Analysis: pria@pleiadesonline.com