Duda, Hart & Stork [Pattern Classification] (2nd ed)

Richard O. Duda, Peter E. Hart, David G. Stork, Pattern Classification (2nd ed-4th print), Wiley-Interscience

official: http://rii.ricoh.com/~stork/DHS.html

publisher: http://as.wiley.com/WileyCDA/WileyTitle/productCd-0471056693.html

google: http://books.google.com/books?id=YoxQAAAAMAAJ

RICHARD O. DUDA

PhD, Professor in the Electrical Engineering Department at San Jose State University, San Jose, California.

PETER E. HART

PhD, Chief Executive Officer and President of Ricoh Innovations, Inc. in Menlo Park, California.

DAVID G. STORK http://rii.ricoh.com/~stork/

PhD, Chief Scientist, also at Ricoh Innovations, Inc.

lectures: 

http://www.stanford.edu/class/ee292d/

http://www.stanford.edu/class/cs229/ (*주목)

cf.

Computer Manual in MATLAB to accompany Pattern Classification, 2nd EditionDavid G. Stork ( Ricoh Silicon Valley ), Elad Yom-Tov, John Wiley & Sons, 2004

http://as.wiley.com/WileyCDA/WileyTitle/productCd-0471429775.html

http://books.google.com/books?id=YxFtQgAACAAJ

loyola: 1관 4층 006.4 S885c 2004

toolbox: http://www.wiley.com/WileyCDA/Section/id-105036.html
download: http://dl.dropbox.com/u/6586316/software/Classification_toolbox.zip

manual: http://www.yom-tov.info/toolbox.html

algorithms: http://www.yom-tov.info/cgi-bin/list_uploaded_files.pl
appendix: http://www.scribd.com/full/23157946?access_key=key-1108q77jeiosgzkqtplz

DAVID G. STORK

PhD, Chief Scientist at Ricoh Innovations, Inc., and Consulting Professor of Electrical Engineering at Stanford University. A graduate of MIT and the University of Maryland, he is the founder and leader of the Open Mind Initiative and the coauthor, with Richard Duda and Peter Hart, of Pattern Classification, Second Edition, as well as four other books.

ELAD YOM-TOV http://www.yom-tov.info/

PhD, research scientist at IBM Research Lab in Haifa, working on the applications of machine learning to search technologies, bioinformatics, and hardware verification (among others). He is a graduate of Tel-Aviv University and the Technion.

Preface

"(Our purpose is) to give a systematic account of the major topics  in pattern recognition, based on fundamental principles"

pattern recognition

speech recognition

optical character recognition

signal classification

pattern classification

scene analysis

machine learning

handwriting & gesture recognition

lipreading

geological analysis

document searching

recognition of bubble chamber tracks of subatomic particles

human-machine interface - eg. pen-based computing

human and animal nervous systems

neurobiology

psychology

"We address a specific class of problems - pattern recognition problems - and consider the wealth of different techniques that can be applied to it."

"We discuss the relative strengths and weaknesses of various classification techniques"

statistical methods vs. syntactic methods

2008/09/03 - [@SG/김경환: Pattern Recognition] - Pattern Classification: ch.1 Introduction