In the sketch symbol adaptive learning, the number of training samples of different users may be different, to keep the number of samples under different good learning effect Fruit become an important issue to be resolved. The draft plan proposed an adaptive character recognition method using the number associated with the classification of training samples Combination strategy will be the template matching method and SVM classification method was efficient statistical combination. It supports a small sample study by using a template matching method And support a large number of samples to learn the SVM method, and sketch symbols while using online information and offline information and achieve a number of different samples of adaptive Learning and recognition of symbols. Based on this method, the paper designed and implemented to support adaptive sketch recognition symbol components. Finally, using the extended PIBG Toolkit developed a prototype system IdeaNote. Is shown th

基于模板匹配和SVM的草图符号自适应识别方法.PDF

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