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Stereo Matching Based on Least Square
Yu Haihao,Fang Yurun,Kong Leilei,Wang Xin 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.2
Least Square method is widely adopted in stereo matching owing to it high precision, but the fact that transformation parameters is obtained by solving linear equations leads to the instability of its solutions and the process of matching oscillates and decreases convergence speed. To overcome this disadvantage, improve convergence speed and keep high precision, this paper provides gradient method to resolve stereo matching. The experiments show that the algorithm is valid and practical.
Prediction of Users Retweet Times in Social Network
Haihao Yu,Xu Feng Bai,ChengZhe Huang,Haoliang Qi 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.5
In view of the fact that the propagation path topology cannot effectively deal with complex social network consists of hundreds of millions of users. More researchers choose to use machine learning methods to complete retweet prediction. Those use the classification method to judge whether a message will be retweeted or not. This paper argues that retweet prediction should be regression analysis problem, not just the classification problem. Through collecting user characteristics on Twitter and selecting some features which have an important impact on the retweet behavior, a Prediction algorithm Based on the Logistic Regression for users Retweet Times in social network was proposed. Experiment results based on the actual data set show the regression analysis predicting model has a good predicting accuracy in dealing with retweet predicting, the proposed method is effectiveness.