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The Gaussian mixture model (GMM) has been widely used in pattern recognition problems for clustering and probability density estimation. Given the number of mixture components (model order), the parameters of GMM can be estimated by the EM algorithm. The model order selection, however, remains an open problem. For classification purpose, we propose a discriminative model selection method to optimize...
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...
Latent semantic indexing (LSI) is an effective technique for feature extraction in text mining, and supervised LSI (SLSI) algorithms have been proposed to exploit the class labels of training data. In this paper, we propose an iterative SLSI framework based on class selection. We show that a previous iterative SLSI algorithm is an instance of the framework. We also propose a method under our framework,...
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum classification error (MCE). This paper proposes a new prototype learning algorithm based on the minimization of a conditional log-likelihood loss (CLL), called log-likelihood of margin (LOGM). A regularization term is added...
In this paper, we present a robust system to accurately detect and localize texts in natural scene images. For text detection, a region-based method utilizing multiple features and cascade AdaBoost classifier is adopted. For text localization, a window grouping method integrating text line competition analysis is used to generate text lines. Then within each text line, local binarization is used to...
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