초록

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Abstract ▼ AI-Helper

Today's mobile devices offer more intuitive touch interfaces and support handwriting recognition. The within class variance of handwritten characters causes the growth of complexity in handwriting recognition as data grows. Because of it, more time and efforts are required to train the recognizer as...

Today's mobile devices offer more intuitive touch interfaces and support handwriting recognition. The within class variance of handwritten characters causes the growth of complexity in handwriting recognition as data grows. Because of it, more time and efforts are required to train the recognizer as data grows. We propose the ensemble method with batch incremental learning. The proposed method adds the new weak learner to ensemble model, when incremental data reaches certain amount. The ensemble method with batch incremental learning reduces the training time of artificial neural network with large data set. It also tends to cancel out overfitting problem caused by high variance.

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