Software fault tolerance technique is used to ensure high reliability. In order to evaluate the quality of fault-tolerant systems, expected execution time and cost must be considered. A new evaluation strategy is prop...
详细信息
Software fault tolerance technique is used to ensure high reliability. In order to evaluate the quality of fault-tolerant systems, expected execution time and cost must be considered. A new evaluation strategy is proposed to evaluate, evaluating the system with three groups of quality factors, which is the capability, the time and the cost. By using them, the system's integrative quality factor can be calculated. When applying this strategy, we compare the quality of software systems which is consist of different fault-tolerant components. The results can be used to improve fault-tolerant system. To achieve the required optimal result, several optimization schemes are given to meet different project demands.
In statistical machine translation (SMT) research, phrase-based methods have been receiving more interest in recent years. In this paper, we first give a brief survey of phrase-based SMT framework, and then make detai...
详细信息
ISBN:
(纸本)9783540709381
In statistical machine translation (SMT) research, phrase-based methods have been receiving more interest in recent years. In this paper, we first give a brief survey of phrase-based SMT framework, and then make detailed comparisons of two typical implementations: alignment template approach and standard phrase-based approach. At last, we propose an improved model to integrate alignment template into standard phrase-based SMT as a new feature in a log-linear model. Experimental results show that our method outperforms the baseline method.
Web image clustering has drawn significant attention in the research community recently. However, not much work has been done in using multi-modal information for clustering Web images. In this paper, we address the p...
详细信息
ISBN:
(纸本)9781595937025
Web image clustering has drawn significant attention in the research community recently. However, not much work has been done in using multi-modal information for clustering Web images. In this paper, we address the problem of Web image clustering by simultaneous integration of visual and textual features from a graph partitioning perspective. In particular, we modelled visual features, images, and words from the surrounding text of the images using a tripartite graph. This graph is actually considered as a fusion of two bipartite graphs that are partitioned simultaneously by the proposed Consistent Isoperimetric High-order Co-clustering(CIHC) framework. Although a similar approach has been adopted before, the main contribution of this work lies in the computational efficiency, quality in Web image clustering and scalab.lity to large image repositories that CIHC is able to achieve. We demonstrate this through experimental results performed on real Web images. Copyright 2007 ACM.
In previous systems of speech emotion recognition, supervised learning are frequently employed to train classifiers on lots of lab.led examples. However, the lab.ling of abundant data requires much time and many human...
详细信息
Image clustering solely based on visual features without any knowledge or background information suffers from the problem of semantic gap. In this paper, we propose SS-NMF: a semi-supervised non-negative matrix factor...
详细信息
ISBN:
(纸本)9781595937025
Image clustering solely based on visual features without any knowledge or background information suffers from the problem of semantic gap. In this paper, we propose SS-NMF: a semi-supervised non-negative matrix factorization framework for image clustering. Accumulated relevance feedback in a CBIR system is treated as user provided supervision for guiding the image clustering. We consider the set of positive images in the feedback as constraints on the clustering specifying that the images "must" be clustered together. Similarly, negative images provide constraints specifying that they "cannot" be clustered along with the positive images. Through an iterative algorithm, we perform symmetric tri-factorization of the image-image similarity matrix to infer the clustering. Theoretically, we prove the correctness of SS-NMF by showing that the algorithm is guaranteed to converge. Through experiments conducted on general purpose image datasets, we demonstrate the superior performance of SS-NMF for clustering images effectively. Copyright 2007 ACM.
In this paper, we suggest an adaptive watermarking method to improve both transparence and robustness of quantization index modulation (QIM) scheme. Instead of a fixed quantization step size, we apply a step size adap...
详细信息
In this paper, we propose a new image codec, which called embedded zerotree wavelet coefficients envelop coding (EZWCEC). The coefficients envelop is characterized by describing the global tendency of the significant ...
详细信息
ISBN:
(纸本)9780819469502
In this paper, we propose a new image codec, which called embedded zerotree wavelet coefficients envelop coding (EZWCEC). The coefficients envelop is characterized by describing the global tendency of the significant wavelet coefficients. Based on the empirical analysis and experimental results, our EZWCEC algorithm restores the trend of the significant wavelet coefficients and estimates the magnitude of some insignificant coefficients on the decoder. Unlike other zerotree coding algorithms such as Said and Pearlman's SPIHT using three lists, EZWCEC only uses two lists during encoding and decoding. So the memory requirement for the hardware implementation is reduced significantly. Although PSNR values for EZWCEC are lower than SPIHT's and JPEG2000's, our experiment results have shown that EZWCEC can dramatically improve the visual quality of reconstructed at low bit rates (e.g., below 0.1bpp).
This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in th...
详细信息
ISBN:
(纸本)9780819469502
This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in the RGB color space and classify each color pixel into noisy pixel or noise-free one, and then employs the standard vector median filtering operations in the detected noisy locations to restore the corrupted pixels and leave the noise-free ones unchanged. The simulation results show that the proposed method excellently suppresses impulsive noise as well as preserving the image details well, and significantly outperforms the existing vector filtering solutions in terms of both the objective measures and the perceptual visual quality.
The great heterogeneity of web based Learning systems storing and providing digital e-learning data requires the introduction of interoperability aspects in order to resolve integration problems in a flexible and dyna...
详细信息
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning strategy. In this paper, we formulate...
详细信息
暂无评论