Journal of Parallel and Distributed Computing
A new scalable parallel DBSCAN algorithm using the disjoint-set data structure
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Scalable parallel OPTICS data clustering using graph algorithmic techniques
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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Fuzzy clustering is an important tool for unsupervised pixel classification in remotely sensed satellite images. In this article, a Simulated Annealing (SA) based fuzzy clustering method is developed and combined with popular Support vector Machine (SVM) classifier to fine tune the clustering produced by SA for obtaining an improved clustering performance. The performance of the proposed technique has been compared with that of some other well-known algorithms for an IRS satellite image of the city of Kolkata and its superiority has been demonstrated quantitatively and visually.