Title :
Candide´s Practical Principles of Experimental Pattern Recognition
Author_Institution :
Department of Computer Science, University of Nebraska, Lincoln, NE 68588.
fDate :
3/1/1983 12:00:00 AM
Abstract :
This correspondence calls attention to several frequently used assumptions and techniques culled from the pattern recognition literature.
Keywords :
Additive noise; Chemical engineering; Chemical technology; Computed tomography; Error analysis; Feature extraction; Image processing; Pattern recognition; Systems engineering and theory; Testing; Classification; feature extraction; image processing; machine intelligence; pattern analysis; pattern recognition;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1983.4767372
