Pattern Analysis and Applications

Aims & Scope

The journal publishes high-quality articles in areas of fundamental research in pattern recognition, machine learning, and their applications in medicine, science, and engineering. The presented research should be analytically and experimentally well tested. In particular, it is essential to verify the quality of the proposed method correctly and compare it with state-of-the-art methods. It is also necessary to ensure that the methods are compared under precisely the same conditions. Thus, all articles should follow the replicable research principle, i.e., the ability for other researchers to repeat the experiment using the same methods and obtain similar results. This ensures the validity and reliability of the original findings. Therefore, providing access to the programming code (e.g., via GitHub) and the data used during the experiments is mandatory.

A twelfth criterion — whether APC fees are clearly disclosed — is not scored here; it is left out of the total rather than counted as a failure. Publication charges appear in the metrics card above.

Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Subject Classification