Adaptive combination of classifiers and its application to handwritten Chinese character recognition

Motivated by the idea of metasynthesis, a new adaptive classifier combination approach is proposed in this paper. Compared with previous integration methods, parameters of the proposed combination approach are dynamically acquired by a coefficient predictor based on neural network and vary with the input pattern. It is also shown that many existing integration schemes can be considered as special cases of the proposed method. This approach is tested in application on handwritten Chinese character recognition. The experimental results demonstrate that this method can result in substantial improvement in overall performance.