Neutrosophic C-means clustering with local information and noise distance-based kernel metric image segmentation-Reference-Cited by-同舟云学术

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Neutrosophic C-means clustering with local information and noise distance-based kernel metric image segmentation

Published:2019-01 Issue: Volume:58 Page:269-276
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Lu Zhenyu,Qiu Yunan,Zhan Tianming

Funder

National Natural Science Foundation of China

Nature Science Foundation of Jiangsu Province

Open Project Program of Key Laboratory of Jiangsu Key Laboratory of Meteorological Observation and Information Processing

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference20 articles.

1. Flickr circles: aesthetic tendency discovery by multi- view regularized topic modeling;Hong;IEEE Trans. Multimed.,2016

2. Unified photo enhancement by discovering aesthetic communities from Flickr;Hong;IEEE Trans. Image Process.,2016

3. Multi-view object retrieval via multi-scale topic models;Hong;IEEE Trans. Image Process.,2016

4. Algorithms for fuzzy clustering;Miyamoto;Studies Fuzziness Soft Comput.,2008

5. Convergence theory for fuzzy c-means: counterexamples and repairs;Bezdek;IEEE Trans. Systems Man Cybernet.,1987

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4. An effective color image segmentation approach using superpixel-neutrosophic C-means clustering and gradient-structural similarity;Optik;2022-06

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