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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 candidates of character patterns are generated by over-segmentation, and sequences of...
A supervised nonlinear classification approach is proposed in this paper. It can classify data in original feature space without concerning kernel transformation to map data into linear high dimension space, Belonging degree measure used in this approach is more rational than some conventional distance measures such as Euclidean distance, Under ERM principle, union of hyper ellipsoids and hyper planes...
This work presents the classification of different types of consumptions of water in a house (sinks, showers, washing machines etc.). This classification takes into account the measured flow and the duration of the flow at a particular point in the water distribution network. The classifier uses the FCM and Gustafson-Kessel algorithms. The data set is called AGUA and it corresponds to real data gathered...
Practical applications of online handwritten character recognition demand robust and highly accurate recognition along with low memory requirements. The Active-DTW classifier proposed by Sridhar et al.combines the advantages of generative and discriminative classifiers to address the similarity of between-class samples, while taking into account the variability of writing styles within the same character...
Human hair has significant effect on the life-likeness of human portrait and human recognition. In this paper, we present a classified method of human hair for hair sketching. We extract shape and appearance features from the training data of hair, including hair raw images and their corresponding sketching templates. Based on these features, we learn twenty-four hairstyles. Given a human hair raw...
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