A 1-NN preclassifier for fuzzy k-NN rule

Proceedings - International Conference on Pattern Recognition

Volumn 4, Issue , 1996, Pages 234-238

  Jozwik, Adam ^a   Chmieleski, Leszek ^b,c   Cudny, Waldemar ^b,c   Sklodowski, Marek ^b,c  

^a INSTITUTE OF BIOCYBERNETICS AND BIOMEDICAL ENGINEERING   (Poland)

^b Association for Image Processing Inc   (Poland)

^c INSTITUTE OF FUNDAMENTAL TECHNOLOGICAL RESEARCH   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

SOFTWARE ENGINEERING;

CLASSIFICATION SCHEME; FUZZY K-NN; LEARNING PROCESS;

PATTERN RECOGNITION;

EID: 4243349003     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.1996.547422     Document Type: Conference Paper

References (8)

1. J. C. Bezdek, S. K. Chuan, and D. Leep. Generalized k-NN rules. Fuzzy Sets and Systems, 18:237-256, 1986.
2. B. V. Dasarathy. Nearest Neighbor (NN) norms: NN pattern classification techniques. IEEE 'Computer Society Press, 1995.
3. P. A. Devijver and J . Kittler. Pattern Recognition: A Statistical Approach. Prentice-Hall, 1982.
4. R. A. Fischer. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 1936.
5. F. Fontana, M. Mari, D. Chetverikov, M. Lugg, T. Postupolski, A. Jbiwik, M. Sklodowski, M. Nieniewski, W. Cudny, and L.Chmielewski. CRAck and SHape defect detection in ferrite cores. 2nd Technical Report of the Project CRASH, CRASH Consortium, Feb 1996.
6. K. Jajuga. The Statistical Pattern Recognition Theory (in Polish). PWN, Warsaw, 1990.
7. A. Joiwik. A learning scheme for a fuzzy k-NN rule. Pattern Recognition Letters, 1:287-289, 1983.
8. G. Z. Yang, P. Burger, D. N. Firmin, and S. R. Underwood. Structure adaptive anisotropic filtering for magnetic resonance image enhancement. In Proc. 6th Int. Conf. CAIP, pages 384-391, Prague, Czech Republic, Sept. 6-8, 1995. Czech Pattern Recognition Society, IAPR, & Czech Technical University, Springer Verlag.