Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Clustering Algorithms
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Extraction of Shift Invariant Wavelet Features for Classification of Images with Different Sizes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture features for DCT-coded image retrieval and classification
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Classification of audio signals using gradient-based fuzzy c-means algorithm with divergence measure
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Centroid Neural Network With a Divergence Measure for GPDF Data Clustering
IEEE Transactions on Neural Networks
Satellite image classification using a divergence-based fuzzy c-means algorithm
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
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Fuzzy c-Means algorithms(FCMs) with different distance measures are applied to an image classification problem in this paper. The distance measures discussed in this paper are the Euclidean distance measure and divergence distance measure. Different distance measures yield different types of Fuzzy c-Means algorithms. Experiments and results on a set of satellite image data demonstrate that the classification model employing the divergence distance measure can archive improvements in terms of classification accuracy over the models using the FCM and SOM algorithms which utilize the Euclidean distance measure.