Description

Containing twenty six contributions by
experts from all over the world, this book
presents both research and review material
describing the evolution and recent
developments of various pattern recognition
methodologies, ranging from statistical,
linguistic, fuzzy-set-theoretic, neural,
evolutionary computing and rough-settheoretic
to hybrid soft computing, with
significant real-life applications.
Pattern Recognition and Big Data provides
state-of-the-art classical and modern
approaches to pattern recognition and
mining, with extensive real life applications.
The book describes efficient soft and
robust machine learning algorithms and
granular computing techniques for data
mining and knowledge discovery: and the
issues associated with handling Big Data.
Application domains considered include
bioinformatics, cognitive machines (or
machine mind developments), biometrics,
computer vision, the e-nose, remote sensing
and social network analysis.