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This paper proposes a method for keyword spotting in offline Chinese handwritten documents using a statistical model. On a text query word, the method measures the similarity between the query word and every candidate word in the document by combining a character classifier and four classifiers characterizing the
This paper presents a text query-based method for keyword spotting from online Chinese handwritten documents. The similarity between a text word and handwriting is obtained by combining the character similiarity scores given by a character classifier. To overcome the ambiguity of character segmentation, multiple
One of the most serious problems that conventional knowledge management (KM) encompasses has been pointed out tardy and ineffective acquisition of knowledge. To resolve this problem, knowledge must be autonomously acquired according to its context of use by applying the technique of keyword extraction in machine
Image classification is an important research topic due to its potential impact on both image processing and understanding. However, due to the inherent ambiguity of image-keyword mapping, this task becomes a challenge. From the perspective of machine learning, image classification task fits the multi-instance
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