Results 21 to 30 of about 3,719,972 (302)
RES-Q: Robust Outlier Detection Algorithm for Fundamental Matrix Estimation
IEEE Access, 2018 Detection of outliers present in noisy images for an accurate fundamental matrix estimation is an important research topic in the field of 3-D computer vision.
Sushil Pratap Bharati +3 more
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Remote Sensing, 2023 A robust multisensor navigation filter design for the entry phase of next-generation Mars entry, descent, and landing (EDL) is presented. The entry phase is the longest and most uncertain portion of a Mars landing sequence. Navigation performance at this
Natnael S. Zewge, Hyochoong Bang
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HOW TO REDUCE DIMENSIONALITY OF DATA: ROBUSTNESS POINT OF VIEW [PDF]
Serbian Journal of Management, 2015 Data analysis in management applications often requires to handle data with a large number of variables. Therefore, dimensionality reduction represents a common and important step in the analysis of multivariate data by methods of both statistics and ...
Jan Kalina, Dita Rensová
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Improving Electronic Sensor Reliability by Robust Outlier Screening
Sensors, 2013 Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount.
Federico Cuesta +1 more
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HIGHLY ROBUST METHODS IN DATA MINING [PDF]
Serbian Journal of Management, 2013 This paper is devoted to highly robust methods for information extraction from data, with a special attention paid to methods suitable for management applications.
Jan Kalina
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A New Estimator: Median of the Distribution of the Mean in Robustness
Mathematics, 2023 In some statistical methods, the statistical information is provided in terms of the values used by classical estimators, such as the sample mean and sample variance.
Alfonso García-Pérez
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Anti-robust and tonsured statistics [PDF]
Model Assisted Statistics and Applications, 2017 This describes a statistical technique called “tonsuring” for exploratory data analysis in finance. Instead of rejecting “outlier” data that conflicts with the model, this strips out “inlier” data to get a clearer picture of how the market changes for larger moves.
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On the behaviour of residual plots in robust regression [PDF]
, 1993 The behaviour of residual plots in robust regression might be distorted by the bias of theı corresponding robust estimator.
Velilla Cerdan, Santiago +1 more
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Frontiers in Psychology, 2013 Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers.
Cyril R Pernet +2 more
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Statistical Procedures and Robust Statistics [PDF]
, 2002 It is argued that a main aim of statistics is to produce statistical procedures which in this article are defined as algorithms with inputs and outputs. The structure and properties of such procedures are investigated with special reference to topological and testing considerations.
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