Recent Advances, Emerging Methods and Applications of Pattern Recognition

Nowadays advanced pattern extraction and analysis techniques have been successfully used in a variety of domains. Nonetheless, many of challenges still exist. In particular, majority of practical applications of pattern recognition are still struggling with huge amounts of the data that exhibits such challenges as concept drift, non-stationary of 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 ability to adapt to constantly changing environment is still a problem. Moreover, problems with heterogeneous and multisource data that require dedicated approach also emerge.