Pattern Analysis and Applications

Aims & Scope

The journal publishes high quality articles in areas of fundamental research in intelligent pattern analysis and applications in computer science and engineering.

It aims to provide a forum for original research which describes novel pattern analysis techniques and industrial applications of the current technology.

In addition, the journal will also publish articles on pattern analysis applications in medical imaging.

The journal solicits articles that detail new technology and methods for pattern recognition and analysis in applied domains including, but not limited to, computer vision and image processing, speech analysis, robotics, multimedia, document analysis, character recognition, knowledge engineering for pattern recognition, fractal analysis, and intelligent control.

The journal publishes articles on the use of advanced pattern recognition and analysis methods including statistical techniques, neural networks, genetic algorithms, fuzzy pattern recognition, machine learning, and hardware implementations which are either relevant to the development of pattern analysis as a research area or detail novel pattern analysis applications.

Papers proposing new classifier systems or their development, pattern analysis systems for real-time applications, fuzzy and temporal pattern recognition and uncertainty management in applied pattern recognition are particularly solicited.

View Aims & Scope

---

Metrics & Ranking

Impact Factor

Year	Value
2025	2
2024	3.70

SJR (SCImago Journal Rank)

Year	Value
2024	0.559

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	66

Journal Rank

Year	Value
2024	10420

Journal Citation Indicator

Year	Value
2024	1039

---

---

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

---

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

---

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks

  Citation: 1166

  Authors: Ali, Ceren, Ziynet

• A survey of graph edit distance

  Citation: 499

  Authors: Xinbo, Bing, Dacheng, Xuelong

• Bagging, Boosting and the Random Subspace Method for Linear Classifiers

  Citation: 417

  Authors: Marina, Robert P. W.

• A review on Gabor wavelets for face recognition

  Citation: 359

  Authors: Linlin, Li

• Limits on the majority vote accuracy in classifier fusion

  Citation: 266

  Authors: L.I., C.J., C.A., R.P.W.

• Combining classifiers: A theoretical framework

  Citation: 260

  Authors: J.

• New Applications of Ensembles of Classifiers

  Citation: 237

  Authors: R., R.M., J.S.

• Optimizing two-pass connected-component labeling algorithms

  Citation: 233

  Authors: Kesheng, Ekow, Kenji

• Dynamic clustering using particle swarm optimization with application in image segmentation

  Citation: 227

  Authors: Mahamed G. H., Ayed, Andries P.

• An empirical study of machine learning techniques for affect recognition in human–robot interaction

  Citation: 226

  Authors: Pramila, Changchun, Nilanjan, Eric

---