Ara
Toplam kayıt 168, listelenen: 11-20
Parallel univariate decision trees
(Elsevier B.V., 2007-05-01)
Univariate decision tree algorithms are widely used in data mining because (i) they are easy to learn (ii) when trained they can be expressed in rule based manner. In several applications mainly including data mining, the ...
Driver recognition using gaussian mixture models and decision fusion techniques
(Springer-Verlag Berlin, 2008)
In this paper we present our research in driver recognition. The goal of this study is to investigate the performance of different classifier fusion techniques in a driver recognition scenario. We are using solely driving ...
The routine design-modular distributed modeling platform for distributed routine design and simulation-based testing of distributed assemblies
(Cambridge University Press, 2008-12-12)
In this paper we describe a conceptual framework and implementation of a tool that supports task-directed, distributed routine design (RD) augmented with simulation-based design testing. In our research, we leverage the ...
Cryptanalysis of image encryption with compound chaotic sequence
(IEEE, 2009)
Recently, an image encryption algorithm based on compound chaotic sequence was proposed [Tong et al., Image and Vision Computing 26 (2008) 843]. In this paper, we analyze the security weaknesses of the proposal. We give ...
A robust biclustering method based on crossing minimization in bipartite graphs
(Springer-Verlag Berlin, 2009)
[No abstract available]
A robust localization framework to handle noisy measurements in wireless sensor networks
(IEEE, 2009-09-14)
We construct a robust localization framework to handle noisy measurements in wireless sensor networks. Traditionally many approaches employ the distance information gathered from ranging devices of the sensor nodes to ...
Calculating the VC-dimension of decision trees
(IEEE, 2009)
We propose an exhaustive search algorithm that calculates the VC-dimension of univariate decision trees with binary features. The VC-dimension of the univariate decision tree with binary features depends on (i) the ...
Fully decentralized, collaborative multilateration primitives for uniquely localizing WSNs
(Springer-Verlag Berlin, 2009)
We provide primitives for uniquely localizing WSN nodes. The goal is to maximize the number of uniquely localized nodes assuming a fully decentralized model of computation. Each node constructs a cluster of its own and ...
Incremental construction of classifier and discriminant ensembles
(Elsevier Science Inc, 2009-04-15)
We discuss approaches to incrementally construct an ensemble. The first constructs an ensemble of classifiers choosing a subset from a larger set, and the second constructs an ensemble of discriminants, where a classifier ...
An incremental model selection algorithm based on cross-validation for finding the architecture of a Hidden Markov model on hand gesture data sets
(IEEE, 2009-12-13)
In a multi-parameter learning problem, besides choosing the architecture of the learner, there is the problem of finding the optimal parameters to get maximum performance. When the number of parameters to be tuned increases, ...