Search results for "Correlation coefficient"
showing 10 items of 166 documents
Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion
2020
Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The inversion results and retrieved values are validated in two ways: A classical machine learning val…
Distance Functions, Clustering Algorithms and Microarray Data Analysis
2010
Distance functions are a fundamental ingredient of classification and clustering procedures, and this holds true also in the particular case of microarray data. In the general data mining and classification literature, functions such as Euclidean distance or Pearson correlation have gained their status of de facto standards thanks to a considerable amount of experimental validation. For microarray data, the issue of which distance function works best has been investigated, but no final conclusion has been reached. The aim of this extended abstract is to shed further light on that issue. Indeed, we present an experimental study, involving several distances, assessing (a) their intrinsic sepa…
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
2020
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…
Isometric endurance test of the cervical flexor muscles - Reliability and normative reference values.
2017
Abstract Objective To obtain reference values for the isometric endurance test (IET) of the cervical flexor muscles, investigate its reproducibility, and compare the results with the maximal isometric strength test (MIST) of the cervical flexor muscles. Design Cross-sectional non-comparative study with single group repeated measurements. Methods Altogether 219 healthy females aged 20–59 years volunteered to participate in the study. The IET was performed in the supine position and MIST seated. The reproducibility was evaluated by the intraclass correlation coefficient (ICC) and an analysis described by Bland and Altman. The relationship between the two measuring methods was evaluated by Pea…
Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology
2021
[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…
A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …
2013
Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…
Is the Kidscreen-27 a valid measure of health-related quality of life in 10-year-old Norwegian children?
2015
The aim of this study was to investigate the reliability and validity of the Norwegian Kidscreen-27 questionnaire, a measure of generic health-related quality of life, in 10 year-old children. The Kidscreen-27 consists of five domains and was validated in a sample of 56 school children (29 boys). The children completed the questionnaire at three different time points during two consecutive school days. For convergent validity, the study was powered to detect a statistically significant correlation coefficient of 0.4. Cronbach's alpha values ranged from 0.73 to 0.83. Floor effects were all zero and ceiling effects ranged from 1.7% to 23.7%. Intraclass correlation values over time ranged from…
Seamless downscaling of the ESA CCI soil moisture data at the daily scale with MODIS land products
2021
Abstract Spatial downscaling has recently become a crucial process in the regional application of coarse-resolution passive microwave surface soil moisture (SSM) products. Extensive gaps in auxiliary optical/thermal infrared observation data (mainly caused by cloud cover) and gaps in coarse-resolution passive microwave SSM data lead to spatiotemporal discontinuity in downscaled SSM maps, thereby limiting their applications. An improved downscaling method for the 25-km European Space Agency (ESA) Climate Change Initiative (CCI) SSM product was proposed to obtain daily seamless downscaled SSM series at a 1-km scale. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra daily land su…
High performance hardware correlation coefficient assessment using programmable logic for ECG signals
2003
Abstract Correlation coefficient is frequently used to obtain cardiac rhythm by peak estimation and appreciate differences in the signal compared to a pattern. This work focuses on the description of a real-time correlation assessment procedure. Applied to electrocardiogram (ECG) signals, a new correlation value is obtained every new sample and pulse detection information is provided. The ECG pattern is internally stored and can be changed when desired. This procedure is useful in Systems on Chip implementation and can be applied to design compact ECG monitoring systems consisting on a system on chip where programmable logic offloads the main processor. A Xilinx FPGA device has been used fo…
A systematic comparison of kinetic modelling methods generating parametric maps for [11C]-(R)-PK11195
2006
[(11)C]-(R)-PK11195 is presently the most widely used radiotracer for the monitoring of microglia activity in the central nervous system (CNS). Microglia, the resident immune cells of the brain, play a critical role in acute and chronic diseases of the central nervous system and in host defence against neoplasia. The purpose of this investigation was to evaluate the reliability and sensitivity of five kinetic modelling methods for the formation of parametric maps from dynamic [(11)C]-(R)-PK11195 studies. The methods we tested were the simplified reference tissue model (SRTM), basis pursuit, a simple target-to-reference ratio, the Logan plot and a wavelet based Logan plot. For the reliabilit…