Results 31 to 40 of about 46,215 (298)
Normality testing after outlier removal
, 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 +2 more sources
Improving K-Means by Outlier Removal [PDF]
, 2005 We present an Outlier Removal Clustering (ORC) algorithm that provides outlier detection and data clustering simultaneously. The method employs both clustering and outlier discovery to improve estimation of the centroids of the generative distribution. The proposed algorithm consists of two stages.
Ville Hautamäki +4 more
openaire +1 more source
Frontiers in Neuroscience, 2023 Data harmonization is a key step widely used in multisite neuroimaging studies to remove inter-site heterogeneity of data distribution. However, data harmonization may even introduce additional inter-site differences in neuroimaging data if outliers are ...
Qichao Han +6 more
doaj +1 more source
A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data
IEEE Access, 2020 Machine learning (ML) is redefining what is possible in data-intensive fields of science and engineering. However, applying ML to problems in the physical sciences comes with a unique set of challenges: scientists want physically interpretable models ...
Kathleen Champion +4 more
doaj +1 more source
Robust Time-of-Arrival Location Estimation Algorithms for Wildlife Tracking
Sensors, 2023 Time-of-arrival transmitter localization systems, which use measurements from an array of sensors to estimate the location of a radio or acoustic emitter, are now widely used for tracking wildlife.
Eitam Arnon +5 more
doaj +1 more source
Adaptive parameter local consistency automatic outlier removal algorithm for area-based matching [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesDue to the influence of image differences and matching methods, geometric calibration of remote sensing images often results in the extraction of control points with inevitable outliers.
T. Huang, H. Pan, N. Zhou
doaj +1 more source
Outlier removal for bird model.
, 2018 A: Bird model with different outliers, B: isolated outlier removal, C: sparse outlier removal, D: non-isolated outlier removal result.
Fan Li (49953) +3 more
core +1 more source
Outlier removal in real-time object recognition and pose estimation [PDF]
, 2019 Outlier removal algorithms aim to detect and remove abnormal or negative data which sufficiently differ from training samples. Since most object recognition or pose estimation methods involve a hypothesise-and-test scheme, especially for large-scale or ...
Shao, Mang
core +1 more source
An Adaptive Group of Density Outlier Removal Filter: Snow Particle Removal from LiDAR Data
, 2022 Light Detection And Ranging (LiDAR) is an important technology integrated into self-driving cars to enhance the reliability of these systems. Even with some advantages over cameras, it is still limited under extreme weather conditions such as heavy rain,
Thanh-Tuan Nguyen +3 more
core +1 more source
High-Speed Outlier Removal Filter for LiDAR Sensor Point Cloud Data
IEEE AccessThis paper proposes an innovative high-speed outlier removal filter designed to efficiently eliminate noise in light detection and ranging (LiDAR) sensor point cloud data, which is essential for real-time autonomous vehicle applications.
Yeun-Sub Byun, Rag-Gyo Jeong
doaj +1 more source