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Titlebook: Advances in Multimedia Information Processing - PCM 2007; 8th Pacific Rim Conf Horace H.-S. Ip,Oscar C. Au,Shi-Min Hu Conference proceeding

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發(fā)表于 2025-3-21 19:54:26 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Multimedia Information Processing - PCM 2007
期刊簡稱8th Pacific Rim Conf
影響因子2023Horace H.-S. Ip,Oscar C. Au,Shi-Min Hu
視頻videohttp://file.papertrans.cn/150/149016/149016.mp4
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advances in Multimedia Information Processing - PCM 2007; 8th Pacific Rim Conf Horace H.-S. Ip,Oscar C. Au,Shi-Min Hu Conference proceeding
影響因子The Pacific-Rim Conference on Multimedia (PCM) was held in Hong Kong, at the City University of Hong Kong, during December 11–14, 2007. Started in 2000, PCM has been held in various places around the Pacific Rim, including Sydney, Beijing, Hsinchu, Singapore, Tokyo, Jeju, and Zhejiang in chronological order. PCM is a major annual international conference organized as a forum for the dissemination of state-of-the-art technological advances and research results in the fields of theoretical, experimental, and applied multimedia analysis and processing. PCM 2007 was organized into 5 different tracks with a total of 247 submissions from 26 countries and regions including Australia, Belgium, Canada, China, Japan, Korea, New Zealand, Singapore, Spain, Taiwan, the UK and the USA. Among the five tracks, “multimedia analysis and retrieval” received the most number of submissions (34% of the submissions). After a rigorous review process, 73 papers were accepted for oral presentations, giving an acceptance rate of under 29% for PCM 2007. In addition, 21 papers were accepted for poster presentations. We would like to thank all the Track Chairs and the reviewers for their timely handling of the
Pindex Conference proceedings 2007
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Veli M?kinen,Simon J. Puglisi,Leena Salmelaemerging AVS system. The decoder system clock is recovered from transport rate info. The audio and video are synchronized according to relative display time info. Some error concealment strategies are also discussed.
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Combinatorial Algebraic Topologyadaptation to different sample distributions and discover the classification in the subspace with na?ve Bayes classifier. FADA overcomes the high computational cost problem of current Adaptive Discriminant Analysis (ADA) and also alleviates the overfitting problem implicitly caused by ADA. FADA is t
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https://doi.org/10.1007/978-3-642-25011-8g positive and negative images. Very often, it is some specific objects or regions in the positive feedback images that the user is really interested in rather than the entire image. This paper presents a hierarchical graphical model for automatically extracting objects and regions that the user is
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Lecture Notes in Computer Scienceever, the SVM-based CBIR always suffers from the problem of the imbalance of image data. Specifically, the number of negative samples (irrelevant images) is far more than that of the positive ones. To deal with this problem, we propose a new active learning approach to enhance the positive sample se
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