Computation Based on Topology
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Recent years have seen a rapid growth in the volume, uncertainty and complexity of electronic data being gathered and stored, for example there are many different medical techniques which produce thousands of medical images per a day. As a result of this increase, the task of extracting meaningful knowledge in the form of patterns, relationships and groupings to be used in applications such as decision support, prediction and taxonomy has become arduous and essential. Furthermore, the need to discover underlying data structures in mixed attribute data calls for efficient data analysis with min...
Recent years have seen a rapid growth in the volume, uncertainty and complexity of electronic data being gathered and stored, for example there are many different medical techniques which produce thousands of medical images per a day. As a result of this increase, the task of extracting meaningful knowledge in the form of patterns, relationships and groupings to be used in applications such as decision support, prediction and taxonomy has become arduous and essential. Furthermore, the need to discover underlying data structures in mixed attribute data calls for efficient data analysis with minimal human intervention. We can say that, mathematical theories are the main tools for achieving these goals. Nowadays, topology is considered a useful and flexible mathematical branch that helps significantly in the field of computation. The cost of manually annotating these data is very high, and recently, research within the field of uncertainty has attracted a lot of attention, such as the field of medical images classification and remote sensing images.
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