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- W2810362504 abstract "A model presented in current paper designed for dynamic classifying of real time cases received in a stream of big sensing data. The model comprises multiple remote autonomous sensing systems; each generates a classification scheme comprising a plurality of parameters. The classification engine of each sensing system is based on small data buffers, which include a limited set of “representative” cases for each class (case-buffers). Upon receiving a new case, the sensing system determines whether it may be classified into an existing class or it should evoke a change in the classification scheme. Based on a threshold of segmentation error parameter, one or more case-buffers are dynamically regrouped into a new composition of buffers, according to a criterion of segmentation quality." @default.
- W2810362504 created "2018-07-10" @default.
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- W2810362504 date "2018-01-01" @default.
- W2810362504 modified "2023-10-17" @default.
- W2810362504 title "Dynamic Classifier and Sensor Using Small Memory Buffers" @default.
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- W2810362504 doi "https://doi.org/10.1007/978-3-319-95786-9_13" @default.
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