By
Konstantinos Koutroumbas, Institute for Space Applications & Remote Sensing, National Observatory of Athens, Greece
Sergios Theodoridis
Sergios Theodoridis
Konstantinos Koutroumbas, Institute for Space Applications & Remote Sensing, National Observatory of Athens, Greece
Description
This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition,
to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition,
have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated
in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback.
Audience:
Electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate
courses on pattern recognition and machine learning. R&D engineers and university researchers in image and signal processing/analyisis,
and computer vision
