Pattern Recognition and artificial intelligence (AI) techniques have been successfully used in a variety of domains. Nonetheless, current challenges still motivate further improvement and scientific efforts. In particular, the majority of practical applications of pattern recognition are still struggling with huge amounts of data that exhibit such challenges as concept drift, non-stationary underlying processes, noise, and common lack of labels or additional metadata that could be useful for further analysis. In addition to that, scalability of those practical applications and the ability to adapt to constantly changing environments still pose problems. Moreover, problems with heterogeneous and multi-source data that require dedicated approaches also emerge. As for AI algorithms, apart from their efficiency, they still require work on fairness, explainability and assurance of fundamental rights and ethical foundations. Therefore, the special issue intends to cover recent solutions to the abovementioned problems, novel methods and algorithms, advances, challenges, as well as practical applications of AI and pattern recognition.

Topics of interest include, but are not limited to:
1. Emerging pattern recognition methods applied to image processing, networks, language processing
and other novel applications
2. Parallelization for pattern recognition and AI
3. Biometric human identification
4. Machine learning for image processing and telecommunications
5. Deep learning and data mining applied to pattern recognition
6. New advancements (architectures, solutions, applied algorithms and methods) for 5G networks, IoT,
Next Generation Infrastructures and SmartGrids
7. Bio-inspired solutions for detection, recognition and security applications
8. Solutions to current emerging problems in image processing and telecommunications
9. Fairness, explainability of AI
10. Secure and adversarial ML
11. Practical applications, especially large-scale