SSPR
2000
Springer
13 years 11 months ago
2000
Springer
Comparisons made in two studies of 21 methods for finding prototypes upon which to base the nearest prototype classifier are discussed. The criteria used to compare the methods are...
SSPR
2000
Springer
13 years 11 months ago
2000
Springer
Abstract. Recently, a number of authors have explored the use of recursive recursive neural nets (RNN) for the adaptive processing of trees or tree-like structures. One of the most...
SSPR
2000
Springer
13 years 11 months ago
2000
Springer
An algorithm for learning structural patterns given in terms of Attributed Relational Graphs (ARG's) is presented. The algorithm, based on inductive learning methodologies, pr...
RSCTC
2000
Springer
13 years 11 months ago
2000
Springer
: This paper presents a Lab. implementation of a computer vision using fuzzy models for pattern recognition for the detection of boundaries in images obtained through a camera inst...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
MCS
2000
Springer
13 years 11 months ago
2000
Springer
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
Various methods exist for reducing correlation between classifiers in a multiple classifier framework. The expectation is that the composite classifier will exhibit improved perfor...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
This paper presents a multi-expert system for dynamic signature verification. The system combines three experts whose complementar behaviour is achieved by using both different fea...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
Abstract. A large experiment on combining classifiers is reported and discussed. It includes, both, the combination of different classifiers on the same feature set and the combina...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...