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Color Extraction Module for Unsupervised Image Classification Representation

Even though working with unlabeled data has the main advantages of lower preprocessing time and resources, the drawback is that the algorithms implemented have no connection between the output and ground truth, therefore is extremely hard to represent the results. This paper proposes a deployable stand-alone module for extracting the real color of the identified classes for a more intuitive representation of the final results.

Alexandru-Toma ANDREI
University "Politehnica"of Bucharest
Romania

Ovidiu GRIGORE
University "Politehnica" of Bucharest
Romania

 


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