Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Granular computing, rough entropy and object extraction
Pattern Recognition Letters
Handbook of Granular Computing
Handbook of Granular Computing
Rough Granular Computing in Knowledge Discovery and Data Mining
Rough Granular Computing in Knowledge Discovery and Data Mining
Standard and Fuzzy Rough Entropy Clustering Algorithms in Image Segmentation
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
The investigation of the Bayesian rough set model
International Journal of Approximate Reasoning
Adaptive Rough Entropy Clustering Algorithms in Image Segmentation
Fundamenta Informaticae
Probabilistic rough entropy measures in image segmentation
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
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Dynamic increase in development of data analysis techniques that has been strengthened and accompanied by recent advances witnessed during widespread development of information systems that depend upon detailed data analysis, requiremore sophisticated data analysis procedures and algorithms. In the last decades, deeper insight into data structure has been more many innovative data analysis approaches have been devised in order to make possible. In the paper, in the Rough Extended Framework, SEM - a new family of the rough entropy based image descriptors has been introduced. The introduced rough entropy based image descriptors are created by means of introduced k-Subspace notion. The Subspace Entropy Maps analysis seems to present potentially robust medium during detailed data analysis. The material has been presented by examples of the introduced solutions as image descriptors