Results 221 to 230 of about 48,550 (262)

Removing outliers by minimizing the sum of infeasibilities

Image and Vision Computing, 2010
This paper shows that we can classify latent outliers efficiently through the process of minimizing the sum of infeasibilities (SOI). The SOI minimization has been developed in the area of convex optimization to find an initial solution, solve a feasibility problem, or check out some inconsistent constraints.
Hyunjung Lee, Yongduek Seo, Sang Wook Lee   +2 more
openaire   +1 more source

Pre-processing of Retinal Images for Removal of Outliers

Wireless Personal Communications, 2020
Early diagnosis of diseases related with retina such as glaucoma is of utmost importance in current scenario as it is the second most prevailing cause of irreversible blindness over the world and is expected to increase further in near future. It is commonly diagnosed using retinal images which are acquired by digital fundus cameras.
Niharika Thakur, Mamta Juneja
openaire   +1 more source

Analytic outlier removal in line fitting

Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), 2002
The conventional ordinary least squares (OLS) method of fitting a line to a set of data points is very unreliable when the amount of random noise in the input (such as an image) is significant compared with the amount of data that is correlated with the lane itself. In this paper we present an analytic method of separating the data of interest from the
Nathan S. Netanyahu, Isaac Weiss
openaire   +1 more source

k -means clustering with outlier removal

Pattern Recognition Letters, 2017
We study the problem of data clustering with outlier detection.We propose a k-means-type algorithm by incorporating an additional cluster into the objective function.The algorithm is able to provide data clustering and outlier detection simultaneously.Outliers are not used in the cluster center calculation.Experiments on synthetic and real data show ...
Guojun Gan, Michael Kwok-Po Ng
openaire   +2 more sources

Guaranteed Outlier Removal for Rotation Search

2015 IEEE International Conference on Computer Vision (ICCV), 2015
Rotation search has become a core routine for solving many computer vision problems. The aim is to rotationally align two input point sets with correspondences. Recently, there is significant interest in developing globally optimal rotation search algorithms. A notable weakness of global algorithms, however, is their relatively high computational cost,
Álvaro Parra Bustos, Tat-Jun Chin
openaire   +2 more sources

Automated Outlier Removal for Mobile Microbenchmarking Datasets

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015
Microbenchmarking is a useful tool for fine-grained performance analysis, and represents a potentially valuable tool in the development of mobile applications and systems. However, the fine-grained measurements of microbenchmarking are inherently susceptible to noise from the underlying operating system and hardware.
Adam Rehn, Jason Holdsworth, Ickjai Lee
openaire   +2 more sources

Removing Outliers Using The L\infty Norm

2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06), 2006
Recently, there has been interest in solving geometric vision problems such as triangulation and camera resectioning using L\infty minimization. One key advantage of using the L\infty norm rather than the L2 norm is that the L\infty cost function has a single minimum unlike the commonly used L2 cost function which typically has multiple local minima ...
Kristy Sim, Richard I. Hartley
openaire   +1 more source

A Multi-Objective Genetic Algorithm for Outlier Removal

Journal of Chemical Information and Modeling, 2015
Quantitative structure activity relationship (QSAR) or quantitative structure property relationship (QSPR) models are developed to correlate activities for sets of compounds with their structure-derived descriptors by means of mathematical models. The presence of outliers, namely, compounds that differ in some respect from the rest of the data set ...
Oren E. Nahum, Abraham Yosipof, Hanoch Senderowitz   +2 more
openaire   +2 more sources

SIGnificant Outlier Removal

Point clouds, usually obtained through scanning or various image processing, are commonly affected by noise and outliers. Such artifacts compromise data quality as they significantly distort subsequent processes, such as normal estimation and surface reconstruction.
Marin, Diana, Ilic, Filip, Ohrhallinger, Stefan, Wimmer, Michael   +3 more
openaire   +1 more source

Outliers Removal and Consolidation of DYNAMIC Point Cloud

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
Recently, there has been increasing interest in the processing of dynamic scenes as captured by 3D scanners, ideally suited for challenging applications such as immersive tele-presence systems and gaming. Despite the fact that the resolution and accuracy of the modern 3D scanners are constantly improving, the captured 3D point clouds are usually noisy ...
Gerasimos Arvanitis, Aristotelis Spathis-Papadiotis, Aris S. Lalos, Konstantinos Moustakas, Nikos Fakotakis   +4 more
openaire   +2 more sources