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Recently, a semi-supervised learning algorithm called ASO (Alternating Structure Optimization) has been proposed, which belongs to linear structural learning. It utilizes a number of auxiliary problems (APs) with unlabelled data and then extracts common structural parameter of APs to improve the performances of the target problems (TPs). How to select the appropriate APs is the keystone of ASO algorithm...
Organizing images into meaningful (semantically) categories using low-level visual features is a challenging and important problem in content-based image retrieval. Clustering algorithms make it possible to represent visual features of images with finite symbols. However, there are two problems in most current image clustering algorithms. One is without considering the choice of the initial cluster...
Organizing images into (semantically) meaningful categories using low-level visual features is a challenging and important problem in content-based image retrieval. Much machine learning methods has been done on automatic semantic image classification. In this paper, we propose a novel approach for semantic classification of images based on weighted feature support vector machine(WFSVM). For image...
Face recognition algorithm based on support vector machines (SVM) have better recognition rate, but the time of training is very long when it have a large number of sample. To overcome this shortcoming, in this paper, the face recognition algorithm based on the proximal SVM (PSVM) was proposed, which the first face image through principal component analysis (PCA) for dimensionality reduction and then...
Chinese Pinyin-to-character conversion is a key technology in Chinese Pinyin input system. In sentence based Pinyin-to-character conversion, segmentation of Pinyin string has important influence on performance of Pinyin-to-character conversion. There are lots of ambiguities in segmentation of Pinyin string. This paper classifies them into overlap and combinational ambiguities, and proposes disambiguation...
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