Search results for "Context"
showing 10 items of 6304 documents
Context-related data processing in artificial neural networks for higher reliability of telerehabilitation systems
2015
Classification is a data processing technique of a great significance both for native eHealth systems and web telemedicine solutions. In this sense, artificial neural networks have been widely applied in telerehabilitation as powerful tools to process information and acquire a new medical knowledge. But effective analysis of multidimensional heterogeneous medical data, still poses considerable difficulties. It was shown that processing too many data features simultaneously is costly and has some adverse effects on the resulting models classification properties. Therefore, there is a strong need to develop new techniques for selecting features from the very large data sets that include many …
Machine learning in remote sensing data processing
2009
Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.
Dimensionality Reduction Techniques: An Operational Comparison On Multispectral Satellite Images Using Unsupervised Clustering
2006
Multispectral satellite imagery provides us with useful but redundant datasets. Using Dimensionality Reduction (DR) algorithms, these datasets can be made easier to explore and to use. We present in this study an objective comparison of five DR methods, by evaluating their capacity to provide a usable input to the K-means clustering algorithm. We also suggest a method to automatically find a suitable number of classes K, using objective "cluster validity indexes" over a range of values for K. Ten Landsat images have been processed, yielding a classification rate in the 70-80% range. Our results also show that classical linear methods, though slightly outperformed by more recent nonlinear al…
Evaluation of a Computer Vision Based Automatic Incident and Congestion Detection System in an Urban Context
1994
Abstract The objective of the document is to describe an Automatic Incident and Congestions Detection System based on computer vision technology, in an urban environment. The document outlines the main technical features of the system and presents the first evaluation results obtained in a field trial currently carried out in protect INVAII) II. within the Transport Telematics Programme of the EC. CCTV cameras are installed in urban street intersections lor surveillance purposes. Based on image processing techniques. the Video Analyzers or Local Sensor Modules (LSM) connected to a number of selected cameras, obtain the traffic status measurements within the field of view of each one of them…
The Analysis of Auxological Data by Means of Nonlinear Multivariate Growth Curves
1999
In this paper we treat the problem to analyse a data set constituted by multivariate growth curves for different subjects; thus in this context we deal with 3-way data tables. Nevertheless, it is not possible using factorial techniques proposed to deal with 3-way data matrices, because the observations are generally not equally spaced; moreover a multilevel approach founded on polynomial models is not suitable to deal with intrinsic nonlinear models. We propose a non-factorial technique to analyse auxological data sets using an intrinsic nonlinear multivariate growth model with autocorrelated errors. The application to a real data set of growing children gave easily interpretable results.
A Little Bird Told Me: Discovering KPIs from Twitter Data
2020
The goal of our research and experiments is to find the definitions and values of key performance indicators (KPIs) in unstructured text. The direct access to opinions of customers served as a motivating factor for us to choose Twitter data for our experiments. For our case study, we have chosen the restaurant business domain. As in the other business domains, KPIs often serve as a solution for identification of current problems. Therefore, it is essential to learn which criteria are important to restaurant guests. The mission of our Proof-of-Concept KPI discovery tool presented in this paper is to facilitate the explorative analysis taking Twitter user posts as a data source. After process…
Scalable Monitoring System for Clouds
2013
Although cloud computing has become an important topic over the last couple of years, the development of cloud-specific monitoring systems has been neglected. This is surprising considering their importance for metering services and, thus, being able to charge customers. In this paper we introduce a monitoring architecture that was developed and is currently implemented in the EASI-CLOUDS project. The demands on cloud monitoring systems are manifold. Regular checks of the SLAs and the precise billing of the resource usage, for instance, require the collection and converting of infrastructure readings in short intervals. To ensure the scalability of the whole cloud, the monitoring system mus…
FABC: Retinal Vessel Segmentation Using AdaBoost
2010
This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…
Fuzzy technique for microcalcifications clustering in digital mammograms
2012
Abstract Background Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could turn out to be very useful in breast cancer control. Methods In this paper we present a potentially powerful microcalcifications cluster enhancement method applicable to digital mammograms. The segmentation phase employs a form filter, obtained from LoG filter, to overcome the dependence from …
La portada de la iglesia de las Escuelas Pías de Gandía. Su proceso constructivo y modulación arquitectónico-musical
2020
The facade of the church of the Pious Schools of Gandia has not attracted the attention of researchers. However, its conception has a great architectural culture and constitutes an essential work to understand its context, fundamentally, that of the theoretical treatises of the Renaissance. From this study it is wanted to value its architecture and that it is considered as an outstanding ingredient to know its period of construction in general and jesuit architecture in particular. For its understanding, its interpretation in the culture of contemporary architecture treaties and, especially, in the architectural-musical theory of Leon Battista Alberti will be necessary.. La portada de la ig…