RECOD at ImageCLEF 2011: Medical Modality Classification using Genetic Programming
نویسندگان
چکیده
This paper describes the participation of the RECOD group on the ImageCLEF 2011 Medical Modality Classification sub-task. We present an approach based on genetic programming and kNN for image classification. In our approach the genetic programming is used for the learning of good functions for the combination of similarities obtained from a set of global descriptors for different visual evidences such as color, texture, and shape. For each class of the dataset a combination function was learned and used as a kNN classifier. Final classification results were generated by a majority voting scheme with the voting functions from each class. Preliminary experiments have shown a good effectiveness of the approach and its potential for improvements.
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