Results 91 to 100 of about 8,729 (215)

RANSAC-LEL: An optimized version with Least Entropy Like Estimators

, 2011
The paper proposes a robust estimation method which implements, in cascade, two algorithms: (i) a Random Sample and Consensus (RANSAC) algorithm and (ii) a novel nonlinear prediction error estimator minimizing a cost function inspired by the mathematical
DISTANTE, Cosimo, Cosimo Distante, INDIVERI, GIOVANNI, G. Indiveri, Giovanni Indiveri, C. Distante   +5 more
core   +1 more source

Research on navigation method in closed-canopy orchard based on 3D LiDAR

Huanan Nongye Daxue xuebao
ObjectiveThe objective of this study is to solve the problem of large longitudinal spacing of fruit trees and the inavailability of global navigation satellite system (GNSS) signals in closed-canopy orchard environment. MethodA navigation method based on
Zhigang ZHANG, Kaiyuan BAO, Wenyu ZHANG, Fan DING, Zongyi TONG, Fukang ZHOU   +5 more
doaj   +1 more source

Least Squares Consensus for Matching Local Features

Information, 2019
This paper presents a new approach to estimate the consensus in a data set. Under the framework of RANSAC, the perturbation on data has not been considered sufficiently.
Qingming Zhang, Buhai Shi, Haibo Xu
doaj   +1 more source

Extended RANSAC Algorithm With Polyline Splitting Approach

, 2022
Bu çalışmanın konusu, genişletilmiş bir Random Sample Consensus (RANSAC) önererek, bu yöntemi iç mekân haritaları üzerinde uygulamaktır. Geleneksel RANSAC algoritması, bir veri kümesinde rasgele seçilen iki örnek arasında çizilen segment ve bu segmente ...
Karakaya, Suat
core  

RANSAC taikymas klaidingiems duomenims aptikti

, 2005
Up-to-date digital photogrammetry involves operations on huge data sets, and with classical image processing procedures it might be time consuming to find out the best solution.
Fröhner, Wolfgang, Ruzgienė, Birutė
core  

Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications

Sensors
The application of LiDAR technology in extracting individual trees and stand parameters plays a crucial role in forest surveys. Accurate identification of individual tree trunks is a critical foundation for subsequent parameter extraction.
Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong   +4 more
doaj   +1 more source

PROBSAC: Probabilistic RANSAC for Sparse Image Denoising

A probabilistic variant of the random sample consensus (RANSAC) algorithm is introduced for sparse image reconstruction under impulsive noise. Classical RANSAC repeatedly samples uniformly random pixel subsets to fit a local model and identify inliers ...
Milos Dakovic, Jonatan Lerga, Milos Brajovic, Isidora Stankovic, Ljubiša Stanković   +4 more
core   +1 more source

Controllable RANSAC-based Anomaly Detection via Hypothesis Testing [PDF]

Detecting the presence of anomalies in regression models is a crucial task in machine learning, as anomalies can significantly impact the accuracy and reliability of predictions.
Phong, Le Hong, Duy, Vo Nguyen Le, Luat, Ho Ngoc   +2 more
core   +1 more source

Beyond RANSAC: User Independent Robust Regression

, 2008
RANSAC is the most widely used robust regression algorithm in computer vision. However, RANSAC has a few drawbacks which make it difficult to use in a lot of applications. Some of these problems have been addressed through improved sampling algorithms or

core  

Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization

Sensors
Industrial computed tomography (CT) is widely used in the measurement field owing to its advantages such as non-contact and high precision. To obtain accurate size parameters, fitting parameters can be obtained rapidly by processing volume data in the ...
Zhe Wang, Jiacheng Hu, Yushu Shi, Jinhui Cai, Lei Pi   +4 more
doaj   +1 more source