Pattern Analysis and Applications is a premier journal focusing on the theory, algorithms, and applications of pattern recognition, computer vision, and machine learning. It serves as a central forum for researchers and practitioners working on innovative methods for analyzing and understanding complex data patterns. The journal fosters interdisciplinary collaboration and aims to bridge the gap between theoretical advances and real-world applications.
Core topics include image and video analysis, object recognition, statistical pattern recognition, neural networks, deep learning, and applications in areas such as biometrics, medical imaging, robotics, and document analysis. The journal is indexed by leading databases such as Scopus and Web of Science. Its target audience is comprised of computer scientists, engineers, statisticians, and researchers involved in artificial intelligence and data science.
Pattern Analysis and Applications encourages submissions that demonstrate the practical impact of pattern analysis techniques in diverse domains. By publishing in this journal, authors contribute to the advancement of this rapidly evolving field and its role in shaping the future of intelligent systems.