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In this paper we propose a novel algorithm to increase the accuracy of the hippocampus segmentation by using the orientation-scale descriptor(OSD) and the sparse coding. The orientation-scale descriptor are high dimensional features which contains image structure information in difference orientations and scales. The method has four steps. Firstly, extract the orientation-scale descriptors and construct...
With the purpose of achieving automated detection of crowd abnormal behavior in public, this paper discusses the category of typical crowd and individual behaviors and their patterns. Popular image features for abnormal behavior detection are also introduced, including global flow based features such as optical flow, and local spatio-temporal based features such as Spatio-temporal Volume (STV). After...
To address the problem of low resolution in surveillance video, which leads to difficulty in recognizing license plates, this paper presents a new license plate image super-resolution reconstruction method based on manifold learning. Firstly, the mapping between low-resolution images and high-resolution images in training set is obtained by learning method. Then image feature vectors are extracted...
In this paper, we present a study of extracting urban areas from Polarimetric Synthetic Aperture Radar (PolSAR) images using only positive samples. We solve this problem by learning a standard binary classifier (urban/non-urban) given an incomplete set of positive samples (urban) and a set of unlabeled samples (some of which are urban and some of which are non-urban) based on the work of Elkan and...
Email spam filtering is considered as an online supervised learning task for binary text classification (TC). Normally, the previous statistical TC algorithms treat an email as a single plain-text document, ignoring the multi-field feature of email documents. This paper investigates the multi-field feature, and proposes a multi-field learning (MFL) approach for email spam filtering. The MFL approach...
This paper proposes a method of identified reciprocating motion in pornographic video from other human action using Hidden Markov Model (HMM). The motion vectors are obtained by decoding the compressed MPEG video. Then the feature vectors are extracted by calculating the direction and the magnitude of the motion vectors. The feature vectors are fed to Hidden Markov Model for training and classification...
Keywords normally carry large amount of category information. In order to fully utilize this kind of information for text classification, this paper proposes a new text feature conversion method based on the SKG model. The method uses the classified texts with the listed key words as the training data to train the classifier. To expand the keyword space, we construct the KWB model and do the text...
The similarity between words is used for word clustering. In spectral clustering algorithms, the information contained in the eigenvectors of an affinity matrix is used to detect the similarity. Compared with traditional clustering methods, spectral clustering performs much better for clustering the words especially in multidimensional vector spaces. the spectral clustering is implemented by Visual...
This paper introduces support vector machine classifiers into entering tone recognition. Not every syllable needs recognition in a statistical way. The recognition accuracy of syllables which need recognition in the support vector machine approach is about 90%, which makes it possible to analyze poems' rhymes and translate Mandarin into many Chinese dialects. The experiments also check the influence...
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