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Issue No. 02 - February (1979 vol. 1)
ISSN: 0162-8828
pp: 193-201
Laveen N. Kanal , FELLOW, IEEE, Department of Computer Science, Laboratory for Pattern Analysis, University of Maryland, College Park, MD 20742.
Noting the major limitations of multivariate statistical classification and syntactic pattern recognition models, this paper presents an overview of some recent work using alternate representations for multistage and nearest neighbor multiclass classification, and for structural analysis and feature extraction. These alternate representations are based on generalizations of state-space and AND/OR graph models and search strategies developed in artificial intelligence (AI). The paper also briefly touches on other current interactions and differences between artificial intelligence and pattern recognition.
Problem-solving, Pattern recognition, Artificial intelligence, Feature extraction, Pattern analysis, Nearest neighbor searches, Computer Society, Computer science, System testing, Heuristic algorithms,state-space graphs, AND/OR graphs, artificial intelligence, feature extraction, multistage statistical classification, nondirectional structural analysis, pattern recognition, problem solving, search
Laveen N. Kanal, "Problem-Solving Models and Search Strategies for Pattern Recognition", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 1, no. , pp. 193-201, February 1979, doi:10.1109/TPAMI.1979.4766905
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