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International Journal of Pattern Recognition and Artificial Intelligence is a peer-reviewed journal published by World Scientific, covering Image Retrieval and Classification Techniques, Advanced Image and Video Retrieval Techniques, Face and Expression Recognition.
| Publisher | World Scientific |
|---|---|
| Reference style | Superscript numbered (World Scientific) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. International Journal of Pattern Recognition and Artificial Intelligence 12, 45–58 (2023).
Formats any DOI in the closest standard style — International Journal of Pattern Recognition and Artificial Intelligence has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Image Retrieval and Classification Techniques Advanced Image and Video Retrieval Techniques Face and Expression Recognition Handwritten Text Recognition Techniques Medical Image Segmentation Techniques |
| ISSN | 0218-0014 |
| Citation impact (2-yr) | 0.77 |
| h-index | 82 |
| i10-index | 1,117 |
| Total citations | 51,734 |
| Top institutions publishing here | Northeastern University |
| Journal website | www.worldscinet.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
This paper describes the development of an algorithm for verification of signatures written on a touch-sensitive pad. The signature verification algorithm is based on an artificial neural network. The novel network presented here, called a “Siamese” time delay neural network, consists of two identical networks joined at their output. During training the network learns to…
Classification of data with imbalanced class distribution has encountered a significant drawback of the performance attainable by most standard classifier learning algorithms which assume a relatively balanced class distribution and equal misclassification costs. This paper provides a review of the classification of imbalanced data regarding: the application domains; the nature of the problem; the learning…
A recent paper posed the question: "Graph Matching: What are we really talking about?". Far from providing a definite answer to that question, in this paper we will try to characterize the role that graphs play within the Pattern Recognition field. To this aim two taxonomies are presented and discussed. The first includes almost all…
We provide a tutorial on learning and inference in hidden Markov models in the context of the recent literature on Bayesian networks. This perspective makes it possible to consider novel generalizations of hidden Markov models with multiple hidden state variables, multiscale representations, and mixed discrete and continuous variables. Although exact inference in these generalizations is…
Cluster ensemble has proved to be a good alternative when facing cluster analysis problems. It consists of generating a set of clusterings from the same dataset and combining them into a final clustering. The goal of this combination process is to improve the quality of individual data clusterings. Due to the increasing appearance of new…
