Search results for " processing"
showing 10 items of 7549 documents
Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data
2018
Density estimation of streaming data is a relevant task in numerous domains. In this paper, a novel non-parametric density estimator called FRONT (forest of normalized trees) is introduced. It uses a structure of multiple normalized trees, segments the feature space of the data stream through a periodically updated linear transformation and is able to adapt to ever evolving data streams. FRONT provides accurate density estimation and performs favorably compared to existing online density estimators in terms of the average log score on multiple standard data sets. Its low complexity, linear runtime as well as constant memory usage, makes FRONT by design suitable for large data streams. Final…
Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods
2019
An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegeta…
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions
2016
The joint density of a data stream is suitable for performing data mining tasks without having access to the original data. However, the methods proposed so far only target a small to medium number of variables, since their estimates rely on representing all the interdependencies between the variables of the data. High-dimensional data streams, which are becoming more and more frequent due to increasing numbers of interconnected devices, are, therefore, pushing these methods to their limits. To mitigate these limitations, we present an approach that projects the original data stream into a vector space and uses a set of representatives to provide an estimate. Due to the structure of the est…
Toward fast and accurate emergency cases detection in BSNs
2020
International audience; In body sensor networks (BSNs), medical sensors capture physiological data from the human body and send them to the coordinator who act as a gateway to health care. The main aim of BSNs is to save peoples' lives. Therefore, fast and correct detection of emergencies while maintaining low-energy consumption of sensors is essential requirement of BSNs. In this study, the authors propose a new adaptive data sampling approach, where the sampling ratio is adapted based on the sensed data variation. The idea is to use the modified version of the cumulative sum (CUSUM) algorithm (modified CUSUM) that they previously proposed for wireless sensor networks to monitor the data v…
The HisClima database: historical weather logs for automatic transcription and information extraction
2021
Knowing the weather and atmospheric conditions from the past can help weather researchers to generate models like the ones used to predict how weather conditions are likely to change as global temperatures continue to rise. Many historical weather records are available from the past registered on a systemic basis. Historical weather logs were registered in ships, when they were on the high seas, recording daily weather conditions such as: wind speed, temperature, coordinates, etc. These historical documents represent an important source of knowledge with valuable information to extract climatic information of several centuries ago. This paper presents a database for researching about the ca…
PDB: A pictorial database oriented to data analysis
1993
The paper describes a new pictorial database oriented to image analysis, implemented inside the MIDAS data analysis system. Pictorial databases need expressive data structures in order to represent a wide class of information from the numerical to the visual. The model of the database is relational; however, a full normalization is not achievable, owing to the complexity of the visual information. The paper reports the general design and notes on the software implementation. Preliminary experiments show the performance of the pictorial database. Copyright © 1993 John Wiley & Sons, Ltd
Reusability and modularity in transactional workflows
1997
Abstract Workflow management techniques have become an intensive area of research in information systems. In large scale workflow systems modularity and reusability of existing task structures with context dependent (parameterized) task execution are essential components of a successful application. In this paper we study the issues related to management of modular transactional workflows, i.e., workflows that reuse component tasks and thus avoid redundancy in design. The notion of parameterized transactional properties of workflow tasks is introduced and analyzed, and the underlying architectural issues are discussed.
Unified computing facility design based on open source software
2012
The article describes e-infrastructure development in Latvia and migration to national Cloud as regional partner facility (RPF) in European Union (EU). In Latvia many public and private Computing Clouds is in operation and problem is how to integrate these resources as one RPF and how to design one unified computing facility that is used for many different applications. The authors offer their solution at Cloud software as a Service and Hardware as a Service level which is based on usage of open source packaged bundles.
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…
Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation.
2019
In this paper, we present a novel convolutional neural network architecture to segment images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed model is an extension of the U-net that embeds a cardiac shape prior and involves a loss function tailored to the cardiac anatomy. Since the shape prior is computed offline only once, the execution of our model is not limited by its calculation. Our system takes as input raw magnetic resonance images, requires no manual preprocessing or image cropping and is trained to segment the endocardium and epicardium of the left ventricle, the endocardium of the right ventricle, as well as the center of the left ventricle. Wit…