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báo cáo hóa học:" Research Article A System for the Semantic Multimodal Analysis of News Audio-Visual Content"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A System for the Semantic Multimodal Analysis of News Audio-Visual Content | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 645052 16 pages doi 10.1155 2010 645052 Research Article A System for the Semantic Multimodal Analysis of News Audio-Visual Content Vasileios Mezaris 1 Spyros Gidaros 1 Georgios Th. Papadopoulos EURASIP Member 1 2 Walter Kasper 3 Jorg Steffen 3 Roeland Ordelman 4 Marijn Huijbregts 4 5 Franciska de Jong 4 loannis Kompatsiaris 1 and Michael G. Strintzis1 2 1 Centre for Research and Technology Hellas Informatics and Telematics Institute 6th Km Charilaou-Thermi Road P.O. BOX 60361 57001 Thermi Greece 2 Department of Electrical and Computer Engineering Aristotle University of Thessaloniki 54006 Thessaloniki Greece 3Language Technology Laboratory DFKI GmbH Stuhlsatzenhausweg 3 66123 Saarbrucken Germany 4Department of Computer Science Human Media Interaction University of Twente 7500 AE Enschede The Netherlands 5 Centre for Language and Speech Technology Radboud University Nijmegen 6525 HT Nijmegen The Netherlands Correspondence should be addressed to Vasileios Mezaris bmezaris@iti.gr Received 24 July 2009 Revised 9 December 2009 Accepted 21 February 2010 Academic Editor Bulent Sankur Copyright 2010 Vasileios Mezaris et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. News-related content is nowadays among the most popular types of content for users in everyday applications. Although the generation and distribution of news content has become commonplace due to the availability of inexpensive media capturing devices and the development of media sharing services targeting both professional and user-generated news content the automatic analysis and annotation that is required for supporting intelligent search and delivery of this content remains an open issue. In this paper a complete architecture for .