Search results for "pattern"
showing 10 items of 4203 documents
New methods for analysing colour texture based on the Karhunen–Loeve transform and quantification
2004
In this article, we offer an original study on the analysis of the texture of colour images based on Local Linear Transforms (LLT). Our colour approach is based on the separability of the data which reduces the number of texture parameters. We also propose the extension of Run Lengths (RL) and Co-occurrence Matrixes (CM) to colour images. In this respect, two different ways were explored (data merging and quantification). We finally present a comparative study showing the efficiency of the first method (LLT) as well as the complementary nature of the other methods (RL, CM).
Learning with the kernel signal to noise ratio
2012
This paper presents the application of the kernel signal to noise ratio (KSNR) in the context of feature extraction to general machine learning and signal processing domains. The proposed approach maximizes the signal variance while minimizes the estimated noise variance in a reproducing kernel Hilbert space (RKHS). The KSNR can be used in any kernel method to deal with correlated (possibly non-Gaussian) noise. We illustrate the method in nonlinear regression examples, dependence estimation and causal inference, nonlinear channel equalization, and nonlinear feature extraction from high-dimensional satellite images. Results show that the proposed KSNR yields more fitted solutions and extract…
Explicit signal to noise ratio in reproducing kernel Hilbert spaces
2011
This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted with PCA, MNF, KPCA, and the previous version of KMNF. Extracted features with the explicit KMNF…
Hyperspectral Image Classification with Kernels
2007
The information contained in hyperspectral images allows the characterization, identification, and classification of land covers with improved accuracy and robustness. However, several critical problems should be considered in the classification of hyperspectral images, among which are (a) the high number of spectral channels, (b) the spatial variability of the spectral signature, (c) the high cost of true sample labeling, and (d) the quality of data. Recently, kernel methods have offered excellent results in this context. This chapter reviews the state-of-the-art hyperspectral image classifiers, presents two recently proposed kernel-based approaches, and systematically discusses the specif…
Gait Analysis Using Multiple Kinect Sensors
2014
A gait analysis technique to model user presences in an office scenario is presented in this chapter. In contrast with other approaches, we use unobtrusive sensors, i.e., an array of Kinect devices, to detect some features of interest. In particular, the position and the spatio-temporal evolution of some skeletal joints are used to define a set of gait features, which can be either static (e.g., person height) or dynamic (e.g., gait cycle duration). Data captured by multiple Kinects is merged to detect dynamic features in a longer walk sequence. The approach proposed here was been evaluated by using three classifiers (SVM, KNN, Naive Bayes) on different feature subsets.
Patterned Model for Technology Development
1997
This paper develops a perspective to modeling patterned technological information flow processes by drawing on concepts from organizational learning and knowledge creation of high technology enterprises. In such a perspective, humans and their interaction in a development team and in an industry’s ‘invisible college’ are modeled as absorbers and users of technological knowledge. The planning behavior of users is specified in terms of design patterns. A hierarchical multilevel pattern flow and repository model is described. Modes for cooperative technology project work in a case of telecommunication industry domain are examined. Questions regarding the relationship between technological know…
On the use of information systems research methods in data mining
2006
Information systems are powerful instruments for organizational problem solving through formal information processing (Lyytinen, 1987). Data mining (DM) and knowledge discovery are intelligent tools that help to accumulate and process data and make use of it (Fayyad, 1996). Data mining bridges many technical areas, including databases, statistics, machine learning, and human-computer interaction. The set of data mining processes used to extract and verify patterns in data is the core of the knowledge discovery process. Numerous data mining techniques have recently been developed to extract knowledge from large databases. The area of data mining is historically more related to AI (Artificial…
Kromos: Ontology based information management for ICT societies
2009
Over the last few years, several projects for the development of innovative systems capable of collecting and sharing information have been carried out, following the increasing companies' interest on a correct knowledge management. ICT companies' managers have realized that knowledge and its management, more than the mere data, constitute fundamental part of their activities. This paper proposes a Knowledge Management System whose main feature is an underlying ontological knowledge representation. This data representation allows the specialization of the reasoning capabilities and the provision of ad hoc behaviors. The system has been designed for the management of projects and processes a…
Collaboration experience in the supply chain of knowledge and patent development
2017
In this paper, we aim at understanding the role of collaboration experience in supply chains of knowledge (SCoK). The SCoK of a company is its supply chain not related to the flow of physical goods but to the flow of R&D commodities. R&D commodities are for example patents, technologies, research services, studies, and projects, and, in high-tech industries, their development and commercialisation are considered as important as real products. To accomplish our aim in this paper, we fulfil the following research objectives: (1) investigate the relationship between the collaboration experience in SCoK and the propensity of the firm to develop new patents; (2) examine how the structural embedd…
A holistic approach to manage environmental quality by using the Kano model and social cognitive theory
2020
International audience; Since its first proposition in 1984, the Kano model has been used extensively in a variety of contexts within industries and academic research demonstrating its wide applicability. The Kano model allows for describing the relationship between an objective aspect and a subjective aspect. Yet is this relevant for environmental quality as well? In this study, we explore the cases where the Kano model is used for assessing environmental quality and its perception by consumers and identify the potential influencing factors for its application with this respect. We find that the Kano model can serve as an effective tool for converging towards environmental quality and sust…