Bibliografías temáticas / Semantic multimedia representation

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Literatura académica sobre el tema "Semantic multimedia representation"

Autor: Grafiati
Publicado: 25 de mayo de 2024
Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Semantic multimedia representation"

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Mylonas, Phivos, Thanos Athanasiadis, Manolis Wallace, Yannis Avrithis, and Stefanos Kollias. "Semantic representation of multimedia content: Knowledge representation and semantic indexing." Multimedia Tools and Applications 39, no. 3 (2007): 293–327. http://dx.doi.org/10.1007/s11042-007-0161-4.

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Zhang, Hong, Yu Huang, Xin Xu, Ziqi Zhu, and Chunhua Deng. "Latent semantic factorization for multimedia representation learning." Multimedia Tools and Applications 77, no. 3 (2017): 3353–68. http://dx.doi.org/10.1007/s11042-017-5135-6.

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Duan, Yiping, Qiyuan Du, Xin Fang, et al. "Multimedia Semantic Communications: Representation, Encoding and Transmission." IEEE Network 37, no. 1 (2023): 44–50. http://dx.doi.org/10.1109/mnet.001.2200468.

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Wagenpfeil, Stefan, Paul Mc Kevitt, and Matthias Hemmje. "Towards Automated Semantic Explainability of Multimedia Feature Graphs." Information 12, no. 12 (2021): 502. http://dx.doi.org/10.3390/info12120502.

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Multimedia feature graphs are employed to represent features of images, video, audio, or text. Various techniques exist to extract such features from multimedia objects. In this paper, we describe the extension of such a feature graph to represent the meaning of such multimedia features and introduce a formal context-free PS-grammar (Phrase Structure grammar) to automatically generate human-understandable natural language expressions based on such features. To achieve this, we define a semantic extension to syntactic multimedia feature graphs and introduce a set of production rules for phrases
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Al-Khatib, W., Y. F. Day, A. Ghafoor, and P. B. Berra. "Semantic modeling and knowledge representation in multimedia databases." IEEE Transactions on Knowledge and Data Engineering 11, no. 1 (1999): 64–80. http://dx.doi.org/10.1109/69.755616.

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Petridis, K., S. Bloehdorn, C. Saathoff, et al. "Knowledge representation and semantic annotation of multimedia content." IEE Proceedings - Vision, Image, and Signal Processing 153, no. 3 (2006): 255. http://dx.doi.org/10.1049/ip-vis:20050059.

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Smith, Roger W., Dorota Kieronska, and Svetha Venkatesh. "Conceptual Representation for Multimedia Information." International Journal of Pattern Recognition and Artificial Intelligence 11, no. 02 (1997): 303–27. http://dx.doi.org/10.1142/s0218001497000147.

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Multimedia information is now routinely available in the forms of text, pictures, animation and sound. Although text objects are relatively easy to deal with (in terms of information search and retrieval), other information bearing objects (such as sound, images, animation) are more difficult to index. Our research is aimed at developing better ways of representing multimedia objects by using a conceptual representation based on Schank's conceptual dependencies. Moreover, the representation allows for users' individual interpretations to be embedded in the system. This will alleviate the probl
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8

Yang, Bo, and Ali R. Hurson. "Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases." Mobile Information Systems 1, no. 4 (2005): 253–73. http://dx.doi.org/10.1155/2005/317136.

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Multimedia data are becoming popular in wireless ad hoc environments. However, the traditional content-based retrieval techniques are inefficient in ad hoc networks due to the multiple limitations such as node mobility, computation capability, memory space, network bandwidth, and data heterogeneity. To provide an efficient platform for multimedia retrieval, we propose to cluster ad hoc multimedia databases based on their semantic contents, and construct a virtual hierarchical indexing infrastructure overlaid on the mobile databases. This content-aware clustering scheme uses a semantic-aware fr
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9

Chang, Xiaojun, Zhigang Ma, Yi Yang, Zhiqiang Zeng, and Alexander G. Hauptmann. "Bi-Level Semantic Representation Analysis for Multimedia Event Detection." IEEE Transactions on Cybernetics 47, no. 5 (2017): 1180–97. http://dx.doi.org/10.1109/tcyb.2016.2539546.

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Jaitly, Shilpa, Vijay Laxmi, and Gagan Jindal. "Content-Based Image Retrieval and Feature Extraction: Analysing the Literature." International Journal for Research Publication and Seminar 15, no. 3 (2024): 357–73. http://dx.doi.org/10.36676/jrps.v15.i3.1520.

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A significant amount of multimedia data consists of digital images, and multimedia content analysis is used in many real-world computer vision applications. Multimedia information, especially photos, has become much more complicated in the last several years. Every day, millions of photos are posted to various websites, such as Instagram, Facebook, and Twitter. Finding a suitable image in an archive is a difficult research subject for the field of computer vision. Most search engines use standard text-based techniques that depend on metadata and captions in order to fetch photos. Over the past
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Tesis sobre el tema "Semantic multimedia representation"

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Harrando, Ismail. "Representation, information extraction, and summarization for automatic multimedia understanding." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS097.

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Que ce soit à la télévision ou sur internet, la production de contenu vidéo connaît un essor sans précédent. La vidéo est devenu non seulement le support dominant pour le divertissement, mais elle est également considérée comme l'avenir de l'éducation, l'information et le loisir. Néanmoins, le paradigme traditionnel de la gestion du multimédia s'avère incapable de suivre le rythme imposé par l'ampleur du volume de contenu créé chaque jour sur les différents canaux de distribution. Ainsi, les tâches de routine telles que l'archivage, l'édition, l'organisation et la recherche de contenu par les
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2

Eze, Emmanuel Uchechukwu. "Context-based multimedia semantics modelling and representation." Thesis, University of Hull, 2013. http://hydra.hull.ac.uk/resources/hull:8004.

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The evolution of the World Wide Web, increase in processing power, and more network bandwidth have contributed to the proliferation of digital multimedia data. Since multimedia data has become a critical resource in many organisations, there is an increasing need to gain efficient access to data, in order to share, extract knowledge, and ultimately use the knowledge to inform business decisions. Existing methods for multimedia semantic understanding are limited to the computable low-level features; which raises the question of how to identify and represent the high-level semantic knowledge in
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3

Zareian, Alireza. "Learning Structured Representations for Understanding Visual and Multimedia Data." Thesis, 2021. https://doi.org/10.7916/d8-94j1-yb14.

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Recent advances in Deep Learning (DL) have achieved impressive performance in a variety of Computer Vision (CV) tasks, leading to an exciting wave of academic and industrial efforts to develop Artificial Intelligence (AI) facilities for every aspect of human life. Nevertheless, there are inherent limitations in the understanding ability of DL models, which limit the potential of AI in real-world applications, especially in the face of complex, multimedia input. Despite tremendous progress in solving basic CV tasks, such as object detection and action recognition, state-of-the-art CV models can
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Libros sobre el tema "Semantic multimedia representation"

1

Anupama, Mallik, and Ghosh Hiranmay, eds. Multimedia ontology: Representation and applications. CRC Press, 2016.

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Mallik, Anupama, Santanu Chaudhury, and Hiranmay Ghosh. Multimedia Ontology: Representation and Applications. Taylor & Francis Group, 2015.

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Mallik, Anupama, Santanu Chaudhury, and Hiranmay Ghosh. Multimedia Ontology: Representation and Applications. Taylor & Francis Group, 2020.

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Mallik, Anupama, Santanu Chaudhury, and Hiranmay Ghosh. Multimedia Ontology: Representation and Applications. Taylor & Francis Group, 2015.

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Capítulos de libros sobre el tema "Semantic multimedia representation"

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Lim, Joo-Hwee. "Semantic Image Representation and Indexing." In Encyclopedia of Multimedia. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_210.

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Dalakleidi, Kalliopi, Stamatia Dasiopoulou, Giorgos Stoilos, Vassilis Tzouvaras, Giorgos Stamou, and Yiannis Kompatsiaris. "Semantic Representation of Multimedia Content." In Knowledge-Driven Multimedia Information Extraction and Ontology Evolution. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20795-2_2.

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Given, No Author. "Towards Semantic Universal Multimedia Access." In Visual Content Processing and Representation. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39798-4_3.

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Carlos, Rafael Paulin, and Kuniaki Uehara. "Video Summarization Based on Semantic Representation." In Advanced Multimedia Content Processing. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48962-2_1.

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Sikos, Leslie F. "Knowledge Representation with Semantic Web Standards." In Description Logics in Multimedia Reasoning. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54066-5_2.

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Giro, Xavier, and Ferran Marques. "From Partition Trees to Semantic Trees." In Multimedia Content Representation, Classification and Security. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11848035_41.

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Wang, Dong, Xiaobing Liu, Duanpeng Wang, Jianmin Li, and Bo Zhang. "SemanGist: A Local Semantic Image Representation." In Advances in Multimedia Information Processing - PCM 2008. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89796-5_64.

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Motik, Boris, Alexander Maedche, and Raphael Volz. "Ontology Representation and Querying for Realizing Semantics-Driven Applications." In Multimedia Content and the Semantic Web. John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470012617.ch2.

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Lin, Chuang, Hongxun Yao, Wei Yu, and Wenbo Tang. "Multi-level Semantic Representation for Flower Classification." In Advances in Multimedia Information Processing – PCM 2017. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77380-3_31.

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Oermann, Andrea, Tobias Scheidat, Claus Vielhauer, and Jana Dittmann. "Semantic Fusion for Biometric User Authentication as Multimodal Signal Processing." In Multimedia Content Representation, Classification and Security. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11848035_72.

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Actas de conferencias sobre el tema "Semantic multimedia representation"

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Cai, Zhicheng, and Qiu Shen. "Encoding Semantic Priors into the Weights of Implicit Neural Representation." In 2024 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2024. http://dx.doi.org/10.1109/icme57554.2024.10688197.

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Araz, Recep Oguz, Dmitry Bogdanov, Pablo Alonso-Jiménez, and Frederic Font. "Evaluation of Deep Audio Representations for Semantic Sound Similarity." In 2024 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2024. https://doi.org/10.1109/cbmi62980.2024.10859250.

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Azough, Ahmed, Alexandre Delteil, Mohand-Said Hacid, and Fabien de Marchi. "A Representation Language for Multimedia Web Semantic." In 2007 2nd International Workshop on Semantic Media Adaptation and Personalization. IEEE, 2007. http://dx.doi.org/10.1109/smap.2007.46.

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Fogarolli, Angela, and Marco Ronchetti. "Domain Independent Semantic Representation of Multimedia Presentations." In 2009 International Conference on Intelligent Networking and Collaborative Systems (INCOS). IEEE, 2009. http://dx.doi.org/10.1109/incos.2009.80.

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Bonino, Dario, Fulvio Corno, and Paolo Pellegrino. "Versatile RDF Representation for Multimedia Semantic Search." In 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007). IEEE, 2007. http://dx.doi.org/10.1109/ictai.2007.129.

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Azough, Ahmed, Alexandre Delteil, Mohand-Said Hacid, and Fabien de Marchi. "A Representation Language for Multimedia Web Semantic." In Second International Workshop on Semantic Media Adaptation and Personalization (SMAP 2007). IEEE, 2007. http://dx.doi.org/10.1109/smap.2007.4414384.

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Lo, Shao-Yuan, and Hsueh-Ming Hang. "Exploring Semantic Segmentation on the DCT Representation." In MMAsia '19: ACM Multimedia Asia. ACM, 2019. http://dx.doi.org/10.1145/3338533.3366557.

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Bu, Xuxiao, Bingfeng Li, Yaxiong Wang, Jihua Zhu, Xueming Qian, and Marco Zhao. "Semantic Gated Network for Efficient News Representation." In ICMR '20: International Conference on Multimedia Retrieval. ACM, 2020. http://dx.doi.org/10.1145/3372278.3390719.

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Jiang, Weiwei. "Research on multimedia representation of IETM based on semantic." In 2012 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE, 2012. http://dx.doi.org/10.1109/icqr2mse.2012.6246503.

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Tang, Pengjie, Hanli Wang, Hanzhang Wang, and Kaisheng Xu. "Richer Semantic Visual and Language Representation for Video Captioning." In MM '17: ACM Multimedia Conference. ACM, 2017. http://dx.doi.org/10.1145/3123266.3127895.

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