Results 251 to 260 of about 4,361,783 (305)

Fingerprint pattern classification

Pattern Recognition, 1984
Abstract This paper presents a new method for fingerprint classification. In this method, fingerprint images are divided into 32 × 32 subregions to obtain direction pattern. Next, the relaxation smoothing process with singularity detection and convergency checking is performed.
Masahiro Kawagoe, Akio Tojo
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Classification with nonexclusive patterns

Proceedings of 13th International Conference on Pattern Recognition, 1996
In this paper, classification problems with N non-mutually exclusive classes are discussed. We introduce a method which can systematically formulate 2/sup n/ mutually exclusive classes without additional training data. We also show that the error rate of the new method is lower than that of the traditional approach when patterns are not mutually ...
Inhao Chang, Murray H. Loew
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Patterns of information classification

Proceedings of the 18th Conference on Pattern Languages of Programs, 2011
Providing efficient access to information can be approached in different ways, but ultimately implies the creation of an Index, represented with an indexing language, like a Taxonomy, a Thesaurus, an Ontology or a Folksonomy. Each of these languages strikes a different balance between the effort to create and maintain the index, the effectiveness of ...
Filipe Figueiredo Correia, Ademar Aguiar
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Classification of Contradiction Patterns

2007
Solving conflicts between overlapping databases requires an understanding of the reasons that lead to the inconsistencies. Provided that conflicts do not occur randomly but follow certain regularities, patterns in the form of “If conditionThenconflict” provide a valuable means to facilitate their understanding.
Heiko Müller 0001, Ulf Leser, Johann Christoph Freytag   +2 more
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Learning pattern classification-a survey

IEEE Transactions on Information Theory, 1998
Summary: Classical and recent results in statistical pattern recognition and learning theory are reviewed in a two-class pattern classification setting. This basic model best illustrates intuition and analysis techniques while still containing the essential features and serving as a prototype for many applications.
Sanjeev R. Kulkarni, Gábor Lugosi, Santosh S. Venkatesh   +2 more
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Classification of meteorological patterns

1997
A classification system which organizes in a restricted number typical meteorological situations, is useful in order to find a relationship between meteorological patterns present in the forecasts and derive local weather parameters. The conventional classifiers based on climatology commonly adopted by weather centres suffer from subjective ...
J. Ambühl, D. Cattani, P. Eckert
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Emerging Patterns and Classification

2000
In this work, we review an important kind of knowledge pattern, emerging patterns (EPs). Emerging patterns are associated with two data sets, and can be used to describe significant changes between the two data sets. To discover all EPs embedded in high-dimension and large-volume databases is a challenging problem due to the number of candidates.
Li, Jinyan, Ramamohanarao, Kotagiri, Dong, Guozhu   +2 more
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An Algorithm for Nonsupervised Pattern Classification

IEEE Transactions on Systems, Man, and Cybernetics, 1973
An algorithm for classifying a data set into an initially unknown number of categories is presented. It is composed of procedure for selecting initial points, a mode estimation procedure, and a classification rule. An integer valued function is defined on the sample space and a gradient search technique is used for estimating its modes. A procedure for
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Interactive Pattern Analysis and Classification

IEEE Transactions on Computers, 1970
This paper describes an on-line interactive graphics system which has been designed to solve the problems of pattern analysis and pattern classification. A wide variety of both classical and unique mathematical algorithms, along with their graphic system implementation, are discussed.
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An Introduction to Pattern Classification

2004
Pattern classification is the field devoted to the study of methods designed to categorize data into distinct classes. This categorization can be either distinct labeling of the data (supervised learning), division of the data into classes (unsupervised learning), selection of the most significant features of the data (feature selection), or a ...
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