A Training-based Optimization Framework for Misclassification Correction
نویسندگان
چکیده
We consider the problem of correcting misclassifications in images by using context based or spatial information. We describe a graph-based method for correcting misclassifications that occur in primary local image recognition. The proposed method is applied in a training-based optimization framework, using genetic algorithms. Numerical simulation results are presented to confirm that once the optimal parameters are obtained by training on one image, satisfactory performance is obtained by using the optimal operator on another significantly different image.
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