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Normality testing after outlier removal [PDF]
, 2023 The cumulant based normality test after outlier removal is analyzed. It is shown that the standard least squares normalizations can be misleading in this context.
Berenguer-Rico, Vanessa +3 more
core +1 more source
NEAR: An artifact removal pipeline for human newborn EEG data
Developmental Cognitive Neuroscience, 2022 Electroencephalography (EEG) is arising as a valuable method to investigate neurocognitive functions shortly after birth. However, obtaining high-quality EEG data from human newborn recordings is challenging.
Velu Prabhakar Kumaravel +3 more
doaj +1 more source
SUPERVISED OUTLIER DETECTION IN LARGE-SCALE MVS POINT CLOUDS FOR 3D CITY MODELING APPLICATIONS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images.
C. Stucker +3 more
doaj +1 more source
Choice of Statistical Tools for Outlier Removal Causes Substantial Changes in Analyte Reference Intervals in Healthy Populations [PDF]
, 2020 BACKGROUND: Reference intervals are an important aid in medical practice as they provide clinicians a guide as to whether a patient is healthy or diseased.Outlier results in population studies are removed by any of a variety of statistical measures.
Cavanaugh, Juleen A +7 more
core +1 more source
An integrated approach for identifying wrongly labelled samples when performing classification in microarray data. [PDF]
PLoS ONE, 2012 Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently.
Yuk Yee Leung +2 more
doaj +1 more source
A Geometric Estimation Technique Based on Adaptive M-Estimators: Algorithm and Applications
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Robust fitting is a basic technique and has been widely applied in photogrammetry and remote sensing, such as geometric correction. As known, typical robust estimators (include M-estimators, S-estimators, MM-estimators, etc.) often fail when outlier rate
Jiayuan Li +3 more
doaj +1 more source
Remote Sensing, 2021 Feature-based remote sensing image registration methods have achieved great accomplishments. However, they have faced some limitations of applicability, automation, accuracy, efficiency, and robustness for large high-resolution remote sensing image ...
Junyan Lu +5 more
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A Method for Removing Outlier Noise from ArrayInSAR Point Clouds based on Hybrid Filtering [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesArray Interferometric Synthetic Aperture Radar (ArrayInSAR) point cloud is a point cloud obtained by three-dimensional imaging of two-dimensional Synthetic Aperture Radar (SAR) images using array interferometric synthetic aperture radar technology, which
F. Ji +6 more
doaj +1 more source
Remote Sensing, 2023 Long-range surveillance and early warning of space targets are significant factors in space security. Under remote observation conditions, the energy performance of the target is weak and subject to environmental and imaging process contamination.
Chenyu Xu +5 more
doaj +1 more source