In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the Knowledge Grid and its distinguished features? What are its methodology...
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We propose an appearance-based image clustering approach called GGCI (global geometric clustering for image). For face images taken with varying pose, expression, eyes (wearing sunglasses or not) or object images unde...
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Barcode has been widely applied in the modern world. This paper presents a fast and robust recognition method of noisy Code 39 barcode. The proposed method can be divided into two steps: search and decoding. In the fi...
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An ideal knowledge flow network passes right knowledge to the right person at the right time. Trust between knowledge nodes influences the efficiency of knowledge interchange in an organization. This paper presents a ...
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A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the ...
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Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content s...
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We propose two geometric structure based approaches GGCI (global geometric clustering for image) and GSIM (geometric structure based image matching) for image clustering and image matching, respectively. For face imag...
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ISBN:
(纸本)9781424404759
We propose two geometric structure based approaches GGCI (global geometric clustering for image) and GSIM (geometric structure based image matching) for image clustering and image matching, respectively. For face images or object images taken with varying factors, the GGCI approach learns the global geometric structure of images space and clusters images based on geodesic distance instead of Euclidean distance and the extended nearest neighbor approach. The GSIM approach uses the minimal Euclidean distance between parts of image and the pattern and its variations as matching criteria and threshold strategy for image matching. We demonstrate experimentally that the GGCI approach achieves lower error rates and the GSIM approach brings down the sensitivity of gray values to change in radiometry and reduces multi local extrema to some extent.
After analyzing the disadvantages of traditional text clustering method based on keywords set, a novel approach for clustering of Chinese text based on concept hierarchy is presented. It introduces a Chinese topic cla...
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Different realistic humanoid motion can be used in vary situations in animation. It also plays an important role in virtual reality. In this paper, we propose a novel method to generate different realistic humanoid mo...
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A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown....
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A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed （MGD） modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeclding algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.
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