Illustration of why identifying outlying points based on the extreme quantiles of the univariate distribution of the markers failed to identify many of the contaminated points.

<p>Illustration of why identifying outlying points based on the extreme quantiles of the univariate distribution of the markers failed to identify many of the contaminated points.</p>

Publication Details

Journal
Figshare
Published
2024-12-02
DOI
https://doi.org/10.1371/journal.pone.0313154.s010
Primary Topic
Image and Object Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Illustration of why identifying outlying points based on the extreme quantiles of the univariate distribution of the markers failed to identify many of the contaminated points.

Figshare
Image and Object Detection Techniques
article

Illustration of why identifying outlying points based on the extreme quantiles of the univariate distribution of the markers failed to identify many of the contaminated points.

article en

Abstract

<p>Illustration of why identifying outlying points based on the extreme quantiles of the univariate distribution of the markers failed to identify many of the contaminated points.</p>

Figshare
Openalex Percentile: Top 64%
Image and Object Detection Techniques
DOISourceOpenAlex
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Illustration of why identifying outlying points based on the extreme quantiles of the univariate distribution of the markers failed to identify many of the contaminated points. · Figshare (2024) | TGRS Research Map | TGRS