Medial-Guided Fuzzy Segmentation

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2000 - Lecture Notes in Computer Science ◽

10.1007/978-3-540-40899-4_23 ◽

2000 ◽

pp. 226-235

Author(s):

George Stetten ◽

Stephen Pizer

Keyword(s):

Fuzzy Segmentation

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Fuzzy segmentation of urban areas in panchromatic remote sensing images

Journal of Computer Applications ◽

10.3724/sp.j.1087.2008.03112 ◽

2009 ◽

Vol 28 (12) ◽

pp. 3112-3115

Author(s):

Yan CHEN ◽

Shou-hong WAN ◽

Yu-chang GONG

Keyword(s):

Remote Sensing ◽

Urban Areas ◽

Remote Sensing Images ◽

Fuzzy Segmentation

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Modified Gath–Geva clustering for fuzzy segmentation of multivariate time-series

Fuzzy Sets and Systems ◽

10.1016/j.fss.2004.07.008 ◽

2005 ◽

Vol 149 (1) ◽

pp. 39-56 ◽

Cited By ~ 87

Author(s):

Janos Abonyi ◽

Balazs Feil ◽

Sandor Nemeth ◽

Peter Arva

Keyword(s):

Time Series ◽

Multivariate Time Series ◽

Fuzzy Segmentation

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MRI Fuzzy Segmentation of Brain Tissue Using Neighborhood Attraction With Neural-Network Optimization

IEEE Transactions on Information Technology in Biomedicine ◽

10.1109/titb.2005.847500 ◽

2005 ◽

Vol 9 (3) ◽

pp. 459-467 ◽

Cited By ~ 220

Author(s):

S. Shen ◽

W. Sandham ◽

M. Granat ◽

A. Sterr

Keyword(s):

Neural Network ◽

Brain Tissue ◽

Network Optimization ◽

Neural Network Optimization ◽

Fuzzy Segmentation

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An Enhanced Fuzzy Segmentation Framework for extracting white matter from T1-weighted MR images

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2021.103093 ◽

2022 ◽

Vol 71 ◽

pp. 103093

Author(s):

S. Vinurajkumar ◽

S. Anandhavelu

Keyword(s):

White Matter ◽

Mr Images ◽

Segmentation Framework ◽

Fuzzy Segmentation

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Fuzzy Segmentation Driven by Modified ABC Algorithm Using Cartilage Features Completed by Spatial Aggregation: Modeling of Early Cartilage Loss

Computational Collective Intelligence - Lecture Notes in Computer Science ◽

10.1007/978-3-319-98446-9_45 ◽

2018 ◽

pp. 479-488 ◽

Cited By ~ 1

Author(s):

Jan Kubicek ◽

Iveta Bryjova ◽

Marek Penhaker ◽

David Oczka ◽

Martin Augustynek ◽

...

Keyword(s):

Spatial Aggregation ◽

Cartilage Loss ◽

Abc Algorithm ◽

Fuzzy Segmentation

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Improve differentiation of Breast mass using fuzzy segmentation method

ZANCO Journal of Pure and Applied Sciences ◽

10.21271/zjpas.29.2.14 ◽

2017 ◽

Vol 29 (2) ◽

Keyword(s):

Breast Mass ◽

Segmentation Method ◽

Fuzzy Segmentation

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Evaluation of Civil Aircraft Safety Status Based on Index Fuzzy Segmentation and MULTIMOORA

2020 IEEE 2nd International Conference on Civil Aviation Safety and Information Technology (ICCASIT ◽

10.1109/iccasit50869.2020.9368514 ◽

2020 ◽

Author(s):

Xiaoqiang Yang ◽

Xiangyi Lin ◽

Lan Jiang

Keyword(s):

Civil Aircraft ◽

Fuzzy Segmentation

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Image Fuzzy Segmentation Using Aggregated Distance Functions and Pixel Descriptors

Artificial Intelligence: Theory and Applications - Studies in Computational Intelligence ◽

10.1007/978-3-030-72711-6_14 ◽

2021 ◽

pp. 255-273

Author(s):

Endre Pap ◽

Ljubo Nedović ◽

Nebojša Ralević

Keyword(s):

Distance Functions ◽

Fuzzy Segmentation

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A Study of Modelling Non-stationary Time Series Using Support Vector Machines with Fuzzy Segmentation Information

Computational Intelligence and Security - Lecture Notes in Computer Science ◽

10.1007/11596448_76 ◽

2005 ◽

pp. 520-527

Author(s):

Shaomin Zhang ◽

Lijia Zhi ◽

Shukuan Lin

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Stationary Time Series ◽

Support Vector ◽

Stationary Time ◽

Vector Machines ◽

Fuzzy Segmentation

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A Fuzzy Segmentation Approach to Guide Marketing Decisions

Fuzzy Methods for Customer Relationship Management and Marketing ◽

10.4018/978-1-4666-0095-9.ch013 ◽

2012 ◽

pp. 291-311

Author(s):

Mònica Casabayó ◽

Núria Agell

Keyword(s):

Artificial Intelligence ◽

Energy Industry ◽

Real Case ◽

Artificial Intelligence Techniques ◽

Segmentation Approach ◽

Fuzzy Segmentation ◽

Realistic Information

The aim of this chapter is to present a fuzzy segmentation model that combines statistical and Artificial Intelligence techniques to identify and quantify multifaceted consumers. One of the primary challenges faced by companies is getting to know their consumers. The latter are increasingly complex, versatile, ever-changing, and even contradictory; in other words, they are multifaceted. There is thus a need for techniques and tools to be able to segment this type of consumer in order to provide companies with the realistic information they need to make the appropriate marketing decisions. A real case study from the Spanish energy industry is included in this chapter to demonstrate the potential of the segmentation model being proposed.

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