Segmentation and reconstruction of polyhedral building roofs from aerial lidar point clouds
This paper presents a solution framework for the segmentation and reconstruction of
polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The …
polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The …
Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation
In this paper, a remote sensing image segmentation procedure that utilizes a single point
iterative weighted fuzzy C-means clustering algorithm is proposed based upon the prior …
iterative weighted fuzzy C-means clustering algorithm is proposed based upon the prior …
An interpretable fuzzy rule-based classification methodology for medical diagnosis
I Gadaras, L Mikhailov - Artificial intelligence in medicine, 2009 - Elsevier
OBJECTIVE: The aim of this paper is to present a novel fuzzy classification framework for the
automatic extraction of fuzzy rules from labeled numerical data, for the development of …
automatic extraction of fuzzy rules from labeled numerical data, for the development of …
Robustness of density-based clustering methods with various neighborhood relations
EN Nasibov, G Ulutagay - Fuzzy Sets and Systems, 2009 - Elsevier
Cluster analysis is one of the most crucial techniques in statistical data analysis. Among the
clustering methods, density-based methods have great importance due to their ability to …
clustering methods, density-based methods have great importance due to their ability to …
Multiclass least-squares support vector machines for analog modulation classification
A Sengur - Expert Systems with Applications, 2009 - Elsevier
This study introduces the usage of multiclass least-squares support vector machines (MC-LS-
SVM) for classification purposes of the analog modulated communication signals. Fulfilled …
SVM) for classification purposes of the analog modulated communication signals. Fulfilled …
A novel k-means algorithm for clustering and outlier detection
Y Zhou, H Yu, X Cai - 2009 Second International Conference …, 2009 - ieeexplore.ieee.org
A three-stage k-means algorithm of O (nkt) polynomial time is proposed to cluster the
numerical data and detect the outliers. The clusters are preliminarily determined at the first …
numerical data and detect the outliers. The clusters are preliminarily determined at the first …
An adaptive system for modelling and simulation of electrical arc furnaces
F Janabi-Sharifi, G Jorjani - Control Engineering Practice, 2009 - Elsevier
Modelling and simulator development for electric arc furnaces (EAFs) are of significant
importance in designing control systems and in performance optimisation of EAFs. This …
importance in designing control systems and in performance optimisation of EAFs. This …
Hydrological modeling using a dynamic neuro-fuzzy system with on-line and local learning algorithm
YST Hong, PA White - Advances in water resources, 2009 - Elsevier
This paper introduces the dynamic neuro-fuzzy local modeling system (DNFLMS) that is
based on a dynamic Takagi–Sugeno (TS) type fuzzy inference system with on-line and local …
based on a dynamic Takagi–Sugeno (TS) type fuzzy inference system with on-line and local …
A multi-plane approach for text segmentation of complex document images
This study presents a new method, namely the multi-plane segmentation approach, for
segmenting and extracting textual objects from various real-life complex document images …
segmenting and extracting textual objects from various real-life complex document images …
Sub clustering K-SVD: size variable dictionary learning for sparse representations
Sparse signal representation from overcomplete dictionaries have been extensively
investigated in recent research, leading to state-of-the-art results in signal, image and video …
investigated in recent research, leading to state-of-the-art results in signal, image and video …