Results 341 to 350 of about 306,098 (388)

Quantifying consistency among interpreters of reference data for estimation of harvest area through visual interpretation of remote sensing data

Forestry: An International Journal of Forest Research
Visual interpretation of remote sensing data is a fundamental procedure for collecting reference data for the accuracy assessment and area estimation of forest disturbance map products.
Katsuto Shimizu, Hideki Saito, Tomoko Furuta, Hiroshi Sasakawa, Tomohiro Seto, Kinryou Mai, Chisato Kanamori, Akihiko Hirano, Nozomi Kanemoto   +8 more
semanticscholar   +1 more source

Bias removal of the reduced complexity channel estimator for OFDM systems with transmit diversity in mobile wireless channels

2010 Second International Conference on Communication Systems, Networks and Applications, 2010
Kuo-Guan Wu, Jer-An Wu
semanticscholar   +1 more source

Bias in the Estimation of Autocorrelations

Biometrika, 1954
Marriott, F. H. C., Pope, J. A.
openaire   +1 more source

BIAS IN AN ESTIMATOR OF THE FRACTIONAL DIFFERENCE PARAMETER

, 1993
Christos Agiakloglou, P. Newbold, M. Wohar   +2 more
semanticscholar   +1 more source

Recursive nonparametric regression estimation for dependent strong mixing functional data

Statistical Inference for Stochastic Processes : An International Journal devoted to Time Series Analysis and the Statistics of Continuous Time Processes and Dynamical Systems, 2020
Y. Slaoui
semanticscholar   +1 more source

On the bias in the AUC variance estimate

Pattern Recognition Letters
The area under the Receiver Operating Characteristic (ROC) curve (AUC) is a standard metric for quantifying and comparing binary classifiers. A popular approach to estimating the AUCs and the associated variabilities - the variance of the AUC or the full covariance matrix of multiple correlated AUCs - is the one proposed by DeLong et al [1], which is ...
openaire   +2 more sources

Bias in Shape Estimation

2004
This paper analyses the uncertainty in the estimation of shape from motion and stereo. It is shown that there are computational limitations of a statistical nature that previously have not been recognized. Because there is noise in all the input parameters, we cannot avoid bias.
Hui Ji, Cornelia Fermüller
openaire   +1 more source

Racial and socioeconomic disparities in lung cancer screening in the United States: A systematic review

Ca-A Cancer Journal for Clinicians, 2021
Ernesto Sosa, Dan J Raz, Virginia Chih-Yi Sun   +2 more
exaly  

A Survey on Bias and Fairness in Machine Learning

ACM Computing Surveys, 2022
Fred Morstatter, Kristina Lerman
exaly  

Plain water consumption in relation to energy intake and diet quality among US adults, 2005-2012.

Journal of human nutrition and dietetics (Print), 2016
R. An, Jennifer J McCaffrey
semanticscholar   +1 more source