IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for clustering data
Algorithms for clustering data
Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A clustering technique based on the distance transform
Pattern Recognition Letters
Minimum Cross-Entropy Approximation for Modeling of Highly Intertwining Data Sets at Subclass Levels
Journal of Intelligent Information Systems
Evidence Accumulation Clustering Based on the K-Means Algorithm
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
A New Cluster Isolation Criterion Based on Dissimilarity Increments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Multiple Clusterings Using Evidence Accumulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Cluster Validity for Data Clustering
Neural Processing Letters
On fuzzy cluster validity indices
Fuzzy Sets and Systems
GAPS: A clustering method using a new point symmetry-based distance measure
Pattern Recognition
A novel similarity measure for data clustering
Intelligent Data Analysis
A cluster validity index for fuzzy clustering
Information Sciences: an International Journal
Robust neural-fuzzy method for function approximation
Expert Systems with Applications: An International Journal
A swarm-inspired projection algorithm
Pattern Recognition
Reconstructing a 3-D structure with multiple deformable solid primitives
Computers and Graphics
Possibilistic shell clustering of template-based shapes
IEEE Transactions on Fuzzy Systems
Clustering: A neural network approach
Neural Networks
An incremental nested partition method for data clustering
Pattern Recognition
Expert Systems with Applications: An International Journal
A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
An information-theoretic fuzzy C-spherical shells clustering algorithm
Fuzzy Sets and Systems
ASOD: Arbitrary shape object detection
Engineering Applications of Artificial Intelligence
Clustering spherical shells by a mini-max information algorithm
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Partitive clustering (K-means family)
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
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A new fuzzy clustering algorithm, designed to detect and characterize ring-shaped clusters and combinations of ring-shaped and compact spherical clusters, has been developed. This FKR algorithm includes automatic search for proper initial conditions in the two cases of concentric and excentric (intersected) combinations of clusters. Validity criteria based on total fuzzy area and fuzzy density are used to estimate the optimal number of substructures in the data set. The FKR algorithm has been tested on a variety of simulated combinations of ring-shaped and compact spherical clusters, and its performance proved to be very good, both in identifying the input shapes and in recovering the input parameters. Application of the FKR algorithm to an MRI image of the heart's left ventricle was used to investigate the possibility of using this algorithm as an aid in image processing.