Ensemble multisensor data using state-of-the-art classification methods

Detection and identification from sensing image is a common task for many applications. In order to improve the performance of detection and identification the use of multiple classifier combination is demonstrated and evaluated in the paper using two industrial image datasets. Experiments show that multiple classifier combination can improve the performance of image classification and image detection and identification with boosting and bagging achieve higher accuracy rates. Accordingly, good performance is consistently derived from static parallel systems.

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