In this paper we introduce a compactness based clustering algorithm. The compactness of a data class is measured by comparing the inter-subset and intra-subset distances. The class compactness of a subset is defined a...
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In this paper we introduce a compactness based clustering algorithm. The compactness of a data class is measured by comparing the inter-subset and intra-subset distances. The class compactness of a subset is defined as the ratio of the two distances. A subset is called an isolated cluster (or icluster) if its class compactness is greater than 1. All iclusters make a containment tree. We introduce monotonic sequences of iclusters to simplify the structure of the icluster tree, based on which a clustering algorithm is designed. The algorithm has the following advantages: it is effective on data sets with clusters nonlinearly separated, of arbitrary shapes, or of different densities. The effectiveness of the algorithm is demonstrated by experiments.
Chiaroscuro in art is characterized by strong contrasts between light and dark. An object in a certain light condition has a certain chiaroscuro pattern in appearance; and this pattern is invariant to the changes of i...
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Chiaroscuro in art is characterized by strong contrasts between light and dark. An object in a certain light condition has a certain chiaroscuro pattern in appearance; and this pattern is invariant to the changes of illumination and pose within a certain extent. In this paper we introduce an object tracking method based on chiaroscuro patterns. The chiaroscuro pattern of an image is computed by running a medial axis transform on selected level sets. The medial axes are pruned and decomposed into segments. These segments make a chiaroscuro pattern. The end points of the segments are collected as key points, which are fed to Kalman filter for object tracking. The effectiveness of the algorithm is demonstrated by experiments.
This paper presents a robust and real time method of license plate localization based on level sets. The proposed algorithm consists of three steps: (1) medial axis transformation of selected level sets, (2) identific...
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This paper presents a robust and real time method of license plate localization based on level sets. The proposed algorithm consists of three steps: (1) medial axis transformation of selected level sets, (2) identification of sub-strokes, and (3) a multi-resolution window-based analysis for plate localization. Experiments show the effectiveness of our algorithm.
One of the most challenging issues in visual information retrieval is retrieval by shape, due to a lack of mathematically rigorous definition of shape similarity. This paper presents a bipolar model for computing shap...
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One of the most challenging issues in visual information retrieval is retrieval by shape, due to a lack of mathematically rigorous definition of shape similarity. This paper presents a bipolar model for computing shape similarity. Given a discrete region, we cut its Voronoi diagram into two parts along the border of the region and each part is a tree. We use the two trees to respectively model the structures of a region and its complement, which is called the Bipolar Model. We prune the two trees by removing the nodes with small protrusions. The leaf nodes of the pruned trees are interleaved to make a leaf chain. Two regions are compared and matched, using a cyclic edit distance between the two leaf chains, with restricted merge and split operations allowed. We tested our algorithm on the MPEG-7 data set and made a “bullseye” score of 89.9%, which is the best performance ever reported.
Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation wit...
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Cross-domain text categorization targets on adapting the knowledge learnt from a labeled source-domain to an unla-beled target-domain, where the documents from the source and target domains are drawn from different di...
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Minimum Error Rate Training (MERT) as an effective parameters learning algorithm is widely applied in machine translation and system combination area. However, there exists an ambiguity problem in respect to the train...
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Minimum Error Rate Training (MERT) as an effective parameters learning algorithm is widely applied in machine translation and system combination area. However, there exists an ambiguity problem in respect to the training goal and it is hard for MERT to tackle, that is different parameters may lead to the same minimum error rate in training but greatly different performances in testing. We propose a novel training objective as the unique goal for training towards, namely partial references, and by use of conditional random fields (CRF) to cast the decoding procedure in system combination as a sequence labeling problem. Experiments on Chinese-English translation test sets show that our approach significantly outperforms the MERT-based baselines with less training time.
In traditional Chinese pulse diagnosis (TCPD), diseases of internal organs can be detected by recognizing pulse waveform patterns of wrist radial arterial. However pulse waveform analysis, for which Doppler diagnosis ...
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In traditional Chinese pulse diagnosis (TCPD), diseases of internal organs can be detected by recognizing pulse waveform patterns of wrist radial arterial. However pulse waveform analysis, for which Doppler diagnosis is a powerful tool, is limited to cardiovascular diseases. This paper tries to fill the gap between TCPD and Doppler diagnosis by applying signal analysis and pattern recognition technologies to Doppler blood flow signals (DBFS's) of wrist radial arterial, which are recorded from both hands of healthy people, gastritis and cholecystitis patients. DBFS's are classified using the features proposed by an L2-soft margin support vector machine (L2-SVM): five clinical Doppler parameters (DP), wavelet energies (WE), wavelet packet energies (WPE), and piecewise axially integrated bispectra (PAIB). 5-fold cross validation is used for performance evaluation. The sick are differentiated from the healthy with an accuracy of about 80% using DP, WE and WPE, while the classification rate between gastritis and cholecystitis reaches 100%. Using PAIB, ether two groups of subjects are classified with accuracy greater than 93%. Gastritis is more accurately recognized than cholecystitis, while the latter is recognized with a higher accuracy on data from the left hand than right. Though the sample size is relatively small, we still argue that the methods proposed here are effective and could serve as an assisstive tool for TCPD.
This paper investigates a subclass of translations between logical systems, called the preservative translations, which preserve the satisfiability and the unsatisfiability of formulas. The definition of preservative ...
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The coordination between agent service and Web service is the key factor for intelligent Web service management in the multi-agent based Web service framework. In view of the drawbacks of existing coordination approac...
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