Bag-of-Words is widely used to describe images for image classification. However, this approach is limited because the spatial relation over visual words is not well exploited and also it is ...difficult to generate a single comprehensive vocabulary. In this paper, we propose novel effective schemes to handle these two issues. First, we propose a structure propagation technique to build more reasonable co-occurrence matrices of visual words to exploit the spatial information, which assigns a higher weight to the co-occurrence over two patches that lie in the same object part. Second, we build the multiple-histogram representation over hierarchical vocabularies to avoid the ambiguity of single vocabulary, and particularly present a learning approach to combine the multiple histograms to integrate both within-vocabulary and cross-vocabulary information. We evaluate our proposed method using the Princeton sports event dataset. Compared to the state-of-the-art results, our proposed approach has shown promising results.
For the purpose of color image segmentation, an unsupervised peak value searching algorithm was proposed, which was used to determine the approximate dominant color components of image. First, the ...local peaks of 3D color histogram within the neighborhood of 3 times 3 times 3 were located. The corresponding color values of local peaks were regarded as initial clustering centers, and the number of local peaks were taken as the number of clustering. In addition, taking into account of the color difference induced by local illumination, the feature vector was constructed including color and texture features. Finally, K-means clustering algorithm was applied to segment the color image. Experiment results show that the proposed method can segment the color image accurately, corresponding with the human visual. Clustering number was determined adaptively, and the problem of over-segmentation was solved effectively. The segmentation result was benefit for the following steps in the computer vision.
Having not the a prior knowledge about the DSSS signal in the non-cooperation condition, we utilize a self-organizing feature map (SOFM) neural network algorithm to detection and identify the PN ...sequence. A new method that is suit DSSS signal is proposed according the Kohonen rule in SOFM theory. Utilizing the characteristic based on non-supervised learning rule, the blind algorithm can estimation the PN sequence in low SNR. The computer simulation and experiment test demonstrated that the algorithm is effective. Comparing the traditional slip-correlation method, the SOFM algorithm's BER and implementation complexity is lower
Electro-optic polymer prism beam deflector Hsiu-Jen Wang; Polishak, B.; Cheng-Sheng Huang ...
LEOS 2008 - 21st Annual Meeting of the IEEE Lasers and Electro-Optics Society,
2008-Nov.
Conference Proceeding
In this paper, the design and fabrication of a prism shape optical beam deflector utilizing a thermoplastic electro-optic polymer are presented. Experimental results of deflection angles versus ...various applied electric fields are investigated.
To develop a scale to assess infectious disease-specific health literacy (IDSHL) in China and test its initial psychometric properties. Methods: Item pooling, reduction and assessment of psychometric ...properties were conducted. The scale was divided into 2 subscales; subscale 1 assessed an individual's skills to prevent/treat infectious diseases and subscale 2 assessed cognitive ability. In 2014, 9000 people aged 15-69 years were randomly sampled from 3 provinces and asked to complete the IDSHL questionnaire. Cronbach's á was calculated to assess reliability. Exploratory factor analysis, t-test, correlations, receiver operating characteristic (ROC) curve and logistic regression were used to examine validity. Results: Each of the 22 items in subscale 1 had a content validity index >0.8. In total, 8858 people completed the scale. The principal components factor analysis suggested a 5-factor solution. All factor loadings were >0.40 ( p<0.05). The IDSHL score was 22.07±7.91 (mean±SD; total score=38.62). Significant differences were observed across age (r=.0.276), sex (males: 21.65±8.03; females: 22.47±7.78), education (14.16±8.19 to 26.55±6.26), 2-week morbidity (present: 20.62±8.17, absent: 22.35±7.83; p<0.001) and health literacy of the highest and lowest 27% score groups (all p<0.05). The ROC curve indicated that 76.2% of respondents were adequate in IDSHL. Binary logistic regression analysis revealed 12 predictors of IDSHL adequacy (p<0.05). Among the 22 remaining items, Corrected Item-Total Correlation ranged from 0.316 to 0.504 and Cronbach's á values ranged from 0.754 to 0.810 if the items were deleted. The overall á value was 0.839 and the difficulty coefficient ranged from 1.19 to 4.08. For subscale 2, there were statistically significant differences between the mean scores of those with a correct/incorrect answer (all p<0.001). Conclusions: The newly developed 28-item scale provides an efficient, psychometrically sound and userfriendly measure of IDSHL in the Chinese population.
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