Results 61 to 70 of about 42,043 (166)

A Maximum Entropy Based Outlier Removal for Airborne LiDAR Point Clouds

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Airborne light detection and ranging (LiDAR) data often suffer from noisy returns hovering in empty space within the collected 3-D point clouds.
Ge Jiang, Derek D. Lichti, Tiangang Yin, Wai Yeung Yan   +3 more
doaj   +1 more source

A Hybrid CUBE-IForest Approach for Outlier Detection in Multibeam Bathymetry

Journal of Marine Science and Engineering
With the rapid development and widespread application of multibeam echo-sounding systems, large-scale and high-resolution seafloor topography can be efficiently acquired, enabling precise mapping of seabed terrain.
Rui Han, Yukai Hong, Xibin Han, Yi Zhang, Shunming Hu, Yuan Huan, Xiaodong Cui, Xiaohu Li   +7 more
doaj   +1 more source

A Maximum Feasible Subsystem for Globally Optimal 3D Point Cloud Registration

Sensors, 2018
In this paper, a globally optimal algorithm based on a maximum feasible subsystem framework is proposed for robust pairwise registration of point cloud data.
Chanki Yu, Da Young Ju
doaj   +1 more source

Robust Stereo Visual Inertial Navigation System Based on Multi-Stage Outlier Removal in Dynamic Environments. [PDF]

Sensors (Basel), 2020
Nam DV, Gon-Woo K.
europepmc   +1 more source

Enhancing Broiler Weight Prediction via Preprocessed Kernel Density Estimation

Agriculture
Accurate broiler weight estimation in commercial farms is hindered by noisy scale data and multi-broiler occupancy. To address this challenge, we propose a KDE-based framework enhanced with systematic preprocessing, including coefficient of variation (CV)
Sangmin Yoo, Yumi Oh, Juwhan Song
doaj   +1 more source

High-Precision Geolocation of SAR Images via Multi-View Fusion Without Ground Control Points

Remote Sensing
Synthetic Aperture Radar (SAR) images generated via range-Doppler (RD) model-based geometric correction often suffer from non-negligible systematic geolocation errors due to cumulative impacts of platform positioning inaccuracies, payload time ...
Anxi Yu, Huatao Yu, Yifei Ji, Wenhao Tong, Zhen Dong   +4 more
doaj   +1 more source

Feature Matching via Self-Adjusting Reliable Correspondence Set and Early Termination

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Feature matching is a fundamental task in remote sensing and 3-D vision. In this article, a new feature matching algorithm is proposed under the random sample consensus (RANSAC) interaction model in which the global RANSAC works on the initial ...
Kuo-Liang Chung, Jui-Che Chang
doaj   +1 more source

GraphDBSCAN: Optimized DBSCAN for Noise-Resistant Community Detection in Graph Clustering

Future Internet
Community detection in complex networks remains a significant challenge due to noise, outliers, and the dependency on predefined clustering parameters.
Danial Ahmadzadeh, Mehrdad Jalali, Reza Ghaemi, Maryam Kheirabadi   +3 more
doaj   +1 more source

Persistence-based clustering with outlier-removing filtration

Frontiers in Applied Mathematics and Statistics
This article describes a non-parametric clustering algorithm with an outlier removal step. Our method is based on tools from topological data analysis: we define a new filtration on metric spaces which is a variant of the Vietoris–Rips filtration that adds information about the points' nearest neighbor to the persistence diagram.
Bois, Alexandre, Tervil, Brian, Oudre, Laurent   +2 more
openaire   +3 more sources

White heteroscedasticty testing after outlier removal

, 2020
Given the effect that outliers can have on regression and specification testing, a vastly used robustification strategy by practitioners consists in: (i) starting the empirical analysis with an outlier detection procedure to deselect atypical data values; then (ii) continuing the analysis with the selected non-outlying observations.
Berenguer Rico, V, Wilms, I
openaire   +1 more source