Now showing items 1-7 of 7
A novel image segmentation approach based on neutrosophic c-means clustering and indeterminacy filtering
This paper presents a novel image segmentation algorithm based on neutrosophic c-means clustering and indeterminacy filtering method. Firstly, the image is transformed into neutrosophic set domain. Then, a new filter, ...
A hybrid dermoscopy images segmentation approach based on neutrosophic clustering and histogram estimation
In this work, a novel skin lesion detection approach, called HBCENCM, is proposed using histogram-based clustering estimation (HBCE) algorithm to determine the required number of clusters in the neutrosophic c-means ...
KNCM: Kernel Neutrosophic c-Means Clustering
Data clustering is an important step in data mining and machine learning. It is especially crucial to analyze the data structures for further procedures. Recently a new clustering algorithm known as 'neutrosophic c-means' ...
Guest editorial: New trends in data pre-processing methods for signal and image classification
[No Abstract Available]
Classification of multi-carrier digital modulation signals using NCM clustering based feature-weighting method
(Elsevier Science Bv, 2019)
This work presents a novel digital modulation signal classification model by combining Neutrosophic c-means (NCM) based feature weighting (NCMBFW) and classifier algorithms. As the digital modulation signal, the multi-carrier ...
A Novel Framework of Two Successive Feature Selection Levels Using Weight-Based Procedure for Voice-Loss Detection in Parkinson & x2019;s Disease
(Ieee-Inst Electrical Electronics Engineers Inc, 2020)
Parkinson & x2019;s disease (PD) is one of the public neuro-degenerative disorders. Speech/voice disorder is considered one of the symptoms at an early stage. Acoustic and speech signal processing methods can potentially ...
OCE-NGC: A neutrosophic graph cut algorithm using optimized clustering estimation algorithm for dermoscopic skin lesion segmentation
Automated skin lesion segmentation is one of the most crucial stages in dermoscopic images based diagnosis. To guarantee efficient unsupervised clustering-based segmentation, a histogram-based clustering estimation (HBCE) ...