Pattern Recognition (journal)

Pattern Recognition (journal)
Title	Pattern Recognition
Discipline	Computer vision; Machine learning
Abbreviation	Pattern Recognit.
Publisher	Elsevier
Country	Netherlands
Frequency	Monthly
History	1968–present
Impact	7.196
Impact-year	2022
Issn	0031-3203

Pattern Recognition (journal) is a peer-reviewed academic journal covering research in Computer vision, Machine learning, Artificial intelligence, Signal processing, and related areas. Published by Elsevier and associated with numerous research institutions such as Massachusetts Institute of Technology, Stanford University, University of Oxford, Carnegie Mellon University, and University of Cambridge, the journal serves as a venue for theoretical advances and empirical studies. Contributors and readers often include investigators from University of California, Berkeley, California Institute of Technology, University of Toronto, ETH Zurich, and Tsinghua University.

History

Established in 1968, the journal emerged during a period of growth in Pattern recognition research influenced by work at Bell Labs, IBM Research, MIT Lincoln Laboratory, SRI International, and RAND Corporation. Early editorial leadership included scholars affiliated with Imperial College London, University College London, Harvard University, and Princeton University. The journal expanded through the 1970s and 1980s alongside developments at venues such as the IEEE Computer Society and the Association for Computing Machinery, and it paralleled milestones at conferences like CVPR, ICCV, NeurIPS, ICML, and ECCV. In the 1990s and 2000s the journal integrated contributions from laboratories at Microsoft Research, Google Research, Facebook AI Research, Apple Machine Learning Research, and Amazon Science.

Scope and Topics

The journal publishes articles on topics intersecting Signal processing and Computer vision including pattern classification methods from Stanford AI Lab-influenced frameworks, statistical learning approaches from University of California, Berkeley, kernel methods popularized at University of Toronto, deep learning architectures developed at Google DeepMind and Facebook AI Research, image segmentation techniques used at Lawrence Livermore National Laboratory, object recognition pipelines from Carnegie Mellon University, feature extraction methods rooted in work at ETH Zurich, and applications in medical imaging from Mayo Clinic and Johns Hopkins University. It also includes research related to biometrics studied at National Institute of Standards and Technology, remote sensing work linked to European Space Agency, and pattern discovery methods investigated at Los Alamos National Laboratory.

Editorial Board and Publication Details

The editorial board comprises editors and associate editors drawn from institutions such as University of Cambridge, Oxford University Press-affiliated scholars, Imperial College London, University of Edinburgh, Peking University, Seoul National University, National University of Singapore, and Australian National University. The publisher, Elsevier, issues the journal monthly with an international reviewer pool including members of IEEE, ACM, Royal Society, and national academies such as the US National Academy of Sciences and the Royal Society of London. Submission and peer-review workflows reference standards used by Nature Research and Science (journal).

Abstracting and Indexing

Pattern Recognition is indexed in major databases and services including Scopus, Web of Science, INSPEC, Compendex, MathSciNet, and the Directory of Open Access Journals metadata records. Citation tracking appears in resources managed by Clarivate, Google Scholar, Microsoft Academic and bibliographic aggregators used by libraries such as the British Library and the Library of Congress.

Impact and Reception

The journal has an established impact factor and is recognized alongside flagship venues like IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research, Neural Computation, and Pattern Recognition Letters. It is cited by researchers from MIT Media Lab, Broad Institute, Wellcome Trust Centre for Human Genetics, Max Planck Institute for Informatics, and Fraunhofer Society. The reception among practitioners in industry labs at NVIDIA Research, Intel Labs, Huawei Noah's Ark Lab, and Baidu Research remains strong, with papers informing development in autonomous driving at Waymo, medical diagnostics at Siemens Healthineers, and remote sensing at Airbus Defence and Space.

Notable Articles and Special Issues

The journal has published influential articles on statistical pattern recognition methodologies stemming from collaborations with Bell Labs, seminal works on image feature descriptors influenced by research at University of British Columbia, and reviews synthesizing progress from conferences like ICCV and ECCV. Special issues have focused on topics connected to workshops at NeurIPS, cross-disciplinary themes involving National Institutes of Health, and themes coordinated with projects funded by the European Research Council and the National Science Foundation.

Access and Publication Model

Published by Elsevier, the journal follows a hybrid subscription and open-access model mirroring policies at Springer Nature and Wiley-Blackwell. Authors may choose open access under agreements similar to transformative arrangements negotiated with consortia such as Projekt DEAL and SCOAP3-style initiatives. Institutional access is provided to universities like Columbia University, Yale University, Princeton University, University of Michigan, and University of Sydney.

Category:Computer science journals Category:Elsevier academic journals