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Brain Tumor Detection in MR Imaging Using DW-MTM Filter and Region-Growing Segmentation Approach
Brain tumor analysis is most challenging and emerging exploration area in medical image processing. For appropriate regimen of brain tumor, early...
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Kernel intuitionistic fuzzy entropy clustering for MRI image segmentation
Fuzzy entropy clustering (FEC) is a variant of hard c-means clustering which utilizes the concept of entropy. However, the performance of the FEC...
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Comparison of Different Fuzzy Clustering Algorithms: A Replicated Case Study
Fuzzy clustering partitions data points of a dataset into clusters in which one data point can belong to more than one cluster. In the literature, a...
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Brain MRI segmentation using initial contour KPCM and optimal speed function for improved level set method
Brain tumors are most aggressive kind of diseases, if left untreated may lead to very short life expectancy. Assessment of these tumors is usually...
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RETRACTED CHAPTER: Lung Cancer Detection with FPCM and Watershed Segmentation Algorithms
Lung malignant growth drives the causes among disease related passing around the world. WHO information showed 1.69 million passing away in 2015. An...
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Robust credibilistic intuitionistic fuzzy clustering for image segmentation
To improve the anti-noise ability of credibilistic intuitionistic fuzzy c-means clustering method (CIFCM) for image segmentation, this paper proposes...
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Online Fuzzy Clustering of Data Streams
Chapter considers new approaches based on computational intelligence methods for solving the tasks of fuzzy clustering-segmentation of data streams...
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Energy Efficient Data Gathering in Wireless Sensor Networks Using Rough Fuzzy C-Means and ACO
Data gathering from inhospitable terrains such as volcanic area, dense forest, sea bed are a major application area of wireless sensor network (WSN)....
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Use of Possibilistic Fuzzy C-means Clustering for Telecom Fraud Detection
This paper presents a novel approach for detecting fraudulent activities in mobile telecommunication networks by using a possibilistic fuzzy c-means...
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Interval Type-2 Fuzzy Possibilistic C-Means Optimization Using Particle Swarm Optimization
In this paper, we present optimization of the Interval Type-2 Fuzzy Possibilistic C-Means (IT2FPCM) algorithm using Particle Swarm Optimization...
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An overview on evolving systems and learning from stream data
Evolving systems unfolds from the interaction and cooperation between systems with adaptive structures, and recursive methods of machine learning....
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A Proposal of Hybrid Fuzzy Clustering Algorithm with Application in Condition Monitoring of Industrial Processes
In this chapter a hybrid algorithm using fuzzy clustering techniques is presented. The algorithm is applied in a condition monitoring scheme with...
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Robust Clustering Algorithms Employing Fuzzy-Possibilistic Product Partition
One of the main challenges in the field of clustering is creating algorithms that are both accurate and robust. The fuzzy-possibilistic product...
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Recognition and Classification of Fruit Diseases Based on the Decomposition of Color Wavelet and Higher-Order Statistical Texture Features
Most of the circumstances, it is to be considered that the forerunners of economic losses and production in the agriculture industry of a country are...
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Comparative Study of Soft Computing Based High-Resolution Satellite Image Segmentation in Additive and User-Oriented Color Space
The satellite image is an assortment of the massive quantity of information for agriculture, environmental assessment and monitoring, map**,...
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Catenary insulator defect detection based on contour features and gray similarity matching
Insulators are the key components of high speed railway catenaries. Insulator failures can cause outages and affect the safe operation of high speed...
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Data optimisation and partitioning in private cloud using dynamic clusters for agricultural datasets
The contemporary soil analytical database processing techniques lack in optimization of databases and tables on storage grids, and are limited to the...
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Performance Assessment for Clustering Techniques for Image Segmentation
The analysis and processing of large datasets is a challenge for researchers. Several approaches have been developed to model these complex data,...
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A Multiple Kernels Interval Type-2 Possibilistic C-Means
In this paper, we propose multiple kernels-based interval type-2 possibilistic c-Means (MKIT2PCM) by using the kernel approach to possibilistic...
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Spatial Possibilistic Fuzzy C-Mean Segmentation Algorithm Integrated with Brain Mid-sagittal Surface Information
A normal human brain holds a high level of bilateral reflection symmetry. On the sagittal view, the brain can be separated into the left and the...
