Results 11 to 20 of about 46,215 (298)
Improved Ellipse Fitting Algorithm with Outlier Removal [PDF]
Jisuanji kexue, 2022 The results of ellipse fitting can be considerably distorted by outliers in the fitted point set.To tackle this problem, three improved ellipse fitting algorithms, one of which is based on least trimmed square, and the other two on dual point removal ...
GUO Si-yu, WU Yan-dong
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CAISOV: Collinear Affine Invariance and Scale-Orientation Voting for Reliable Feature Matching
Remote Sensing, 2022 Reliable feature matching plays an important role in the fields of computer vision and photogrammetry. Due to the complex transformation model caused by photometric and geometric deformations, and the limited discriminative power of local feature ...
Haihan Luo +5 more
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STAR_outliers: a python package that separates univariate outliers from non-normal distributions
BioData Mining, 2023 There are not currently any univariate outlier detection algorithms that transform and model arbitrarily shaped distributions to remove univariate outliers.
John T. Gregg, Jason H. Moore
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Nearest Centroid Classifier with Outlier Removal for Classification
JITeCS (Journal of Information Technology and Computer Science), 2020 Classification method is misled by outlier. However, there are few research of classification with outlier removal, especially for Nearest Centroid Classifier Method. The proposed methodology consists of two stages.
Aditya Hari Bawono +2 more
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Journal of Medical Internet Research, 2023 BackgroundReference intervals (RIs) play an important role in clinical decision-making. However, due to the time, labor, and financial costs involved in establishing RIs using direct means, the use of indirect methods, based on ...
Dan Yang +10 more
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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
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IEEE Access, 2022 The software engineering researchers have worked on different dimensions to facilitate better software effort estimates, including those focusing on dataset quality improvement.
Swarnima Singh Gautam, Vrijendra Singh
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An adaptive outlier removal aided k-means clustering algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 K-means is one of ten popular clustering algorithms. However, k-means performs poorly due to the presence of outliers in real datasets. Besides, a different distance metric makes a variation in data clustering accuracy. Improve the clustering accuracy of
Nawaf H.M.M. Shrifan +2 more
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SPATIAL ANALYSIS FOR OUTLIER REMOVAL FROM LIDAR DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 Outlier detection in LiDAR point clouds is a necessary process before the subsequent modelling. So far, many studies have been done in order to remove the outliers from LiDAR data.
A. A. Matkan +4 more
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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
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