Literatura académica sobre el tema "Multimedia Optimization"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Multimedia Optimization".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Artículos de revistas sobre el tema "Multimedia Optimization"
Aggarwal, Charu C., Joel L. Wolf y Philip S. Yu. "Optimization issues in multimedia systems". International Journal of Intelligent Systems 13, n.º 12 (diciembre de 1998): 1113–35. http://dx.doi.org/10.1002/(sici)1098-111x(199812)13:12<1113::aid-int3>3.0.co;2-o.
Texto completoHrabovskyi, Yevhen y Volodymyr Fedorchenko. "DEVELOPMENT OF THE OPTIMIZATION MODEL OF THE INTERFACE OF MULTIMEDIA EDITION". EUREKA: Physics and Engineering 3 (31 de mayo de 2019): 3–12. http://dx.doi.org/10.21303/2461-4262.2019.00902.
Texto completoGarofalakis, Minos N. y Yannis E. Ioannidis. "Scheduling issues in multimedia query optimization". ACM Computing Surveys 27, n.º 4 (diciembre de 1995): 590–92. http://dx.doi.org/10.1145/234782.234797.
Texto completoHuang, Jianwei, Zhu Li y Qian Zhang. "Collaboration and Optimization for Multimedia Communications". Advances in Multimedia 2008 (2008): 1–2. http://dx.doi.org/10.1155/2008/720685.
Texto completoLu, Jingrong. "Optimization Simulation of Balanced Distribution of Multimedia Network Modular Teaching Resources". Mobile Information Systems 2022 (14 de septiembre de 2022): 1–10. http://dx.doi.org/10.1155/2022/5348953.
Texto completoFeng, Wei Wei. "Multi-objective Optimization Algorithm for Multimedia English Teaching (MOAMET) Based on Computer Network Traffic Prediction Model". International Journal of Emerging Technologies in Learning (iJET) 13, n.º 03 (5 de marzo de 2018): 58. http://dx.doi.org/10.3991/ijet.v13i03.8372.
Texto completoHeng, Shao. "A New Intelligent Optimization Network Online Learning Behavior in Multimedia Big Data Environment". International Journal of Mobile Computing and Multimedia Communications 8, n.º 3 (julio de 2017): 21–31. http://dx.doi.org/10.4018/ijmcmc.2017070102.
Texto completoZelenin, A. N. y M. L. Jusupov. "Optimization of usage of the multimedia equipment". E3S Web of Conferences 282 (2021): 07012. http://dx.doi.org/10.1051/e3sconf/202128207012.
Texto completoTaboada, Ianire, Fidel Liberal, Jose Oscar Fajardo y Urtzi Ayesta. "QoE–aware optimization of multimedia flow scheduling". Computer Communications 36, n.º 15-16 (septiembre de 2013): 1629–38. http://dx.doi.org/10.1016/j.comcom.2013.06.007.
Texto completoSafadi, Bahjat, Nadia Derbas y Georges Quénot. "Descriptor optimization for multimedia indexing and retrieval". Multimedia Tools and Applications 74, n.º 4 (17 de mayo de 2014): 1267–90. http://dx.doi.org/10.1007/s11042-014-2071-6.
Texto completoTesis sobre el tema "Multimedia Optimization"
Aksoy, Cumhur Ercument. "Wireless thin client optimization for multimedia applications". [Florida] : State University System of Florida, 2000. http://etd.fcla.edu/etd/uf/2000/amt2363/Tez3.pdf.
Texto completoTitle from first page of PDF file. Document formatted into pages; contains xii, 154 p.; also contains graphics. Vita. Includes bibliographical references (p. 152-153).
Elaine, Wen Y. N. "Multimedia communication performance optimization on Pentium III processor". Thesis, The University of Sydney, 2000. https://hdl.handle.net/2123/28559.
Texto completoSezer, Osman Gokhan. "Data-driven transform optimization for next generation multimedia applications". Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42765.
Texto completoYerima, Suleiman Y. "Quality of service optimization of multimedia traffic in mobile networks". Thesis, University of South Wales, 2009. https://pure.southwales.ac.uk/en/studentthesis/quality-of-service-optimization-of-multimedia-traffic-in-mobile-networks(975989e3-30f0-450b-9c6f-c2c51362f380).html.
Texto completoANEDDA, MATTEO. "QOS OPTIMIZATION FOR MULTIMEDIA DELIVERY CONTENT OVER HETEROGENEOUS WIRELESS NETWORKS". Doctoral thesis, Università degli Studi di Cagliari, 2017. http://hdl.handle.net/11584/249553.
Texto completoRahman, Tasnim. "Optimization of Cross-Layer Network Data based on Multimedia Application Requirements". Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-theses/1348.
Texto completoKim, Ilseo. "Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting". Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52152.
Texto completoXu, Qing. "Flexible Radio Resource Management for Multicast Multimedia Service Provision : Modeling and Optimization". Thesis, Belfort-Montbéliard, 2014. http://www.theses.fr/2014BELF0237/document.
Texto completoThe high throughputs supported by the multimedia multicast services (MBMS) and the limited radio resources result in strong requirement for efficient radio resource management (RRM) in UMTS 3G networks. This PhD thesis proposes to solve the MBMS RRM problem as a combinatorial optimization problem. The work starts with a formal modeling of the problem, named as the Flexible Radio Resource Management Model (F2R2M). An in-depth analysis of the problem complexity and the search landscape is done from the model. It is showed that, by relaxing the OVSF code constraints, the MBMS RRM problem can be approximated as a Multiple-Choice Knapsack Problem (MCKP). Such work allows us to compute the theoretical solution bounds by solving the approximated MCKP. Then the fitness landscape analysis shows that the search spaces are rough and reveal several local optimums. Based on the analysis, some metaheuristic algorithms are studied to solve the MBMS RRM problem. We first show that a Greedy Local Search (GLS) and a Simulated Annealing (SA) allow us to find better solutions than the existing approaches implemented in the UMTS system, however the results are instable due to the landscape roughness. Finally we have developed a Tabu Search (TS) mixed with a Variable Neighborhood Search (VNS) algorithm and we have compared it with GLS, SA and UMTS embedded algorithms. Not only the TS outperforms all the other approaches on several scenarios but also, by comparing it with the theoretical solution bounds generated by the MCKP solver, we observe that TS is equal or close to the theoretical optimal solutions
Ribeiro, Leila Zurba. "Traffic Dimensioning for Multimedia Wireless Networks". Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/27199.
Texto completoPh. D.
Khernane, Nesrine. "Collaborative multimedia sensors for a connected and smart city". Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD027.
Texto completoDue to their high application potential in various innovative fields (telemonitoring, telemedicine, etc.), Wireless Multimedia Sensor Networks (WMSN) arouse the interest of numerous research projects. In addition to inherent constraints of scalar sensor networks in terms of energy limitation, deployment, coverage, reliability, ..., WMSNs impose new constraints related to the captured data. Indeed, multimedia data are very voluminous in comparison to scalar data and, in addition, have a time constraint (real-time delivery). Moreover, their semantic content, very rich, is subject to different perceptions and interpretations depending on the quality of the acquisition. As a target application, this dissertation focuses detecting available car parking spaces within a large city or a metropolis. Nevertheless, the proposed approaches can be used for a wide variety of WMSN applications for surveillance purposes.In this context, the main objective remains the network lifetime maximization while ensuring an acceptable perceived quality at the destination station. The studied approaches are of a distributed nature for scalability reasons, required in WMSN. Two main axes have been targeted: data processing at source nodes and data routing toward the destination.In the data processing axis, the main problem lies in the quality of the data to be transmitted. In general, the higher the quality is, the larger the data are, and consequently more important is the energy consumption and vice versa. It is therefore a question of finding a balance that preserve the energy resources; i.e. maximize the network lifetime while ensuring an acceptable quality of the sent data. The latter is the result of an encoding process at the source level.Thus, we proposed a fully distributed algorithm that maximizes the network lifetime by optimally balancing the encoding power and the source rate at the source node in order to meet a desired visual quality at the destination station. In opposition to existing approaches, our algorithm, of distributed nature, is ensured to find such a trade-off whatever the initial network configuration is.As a second step, we focuses on data routing. In fact, due to the complexity of this problem, especially in a decentralized context, literature works have not considered jointly data processing and routing. In other words, routing was considered as a network input.In the research work of this thesis, we have subsequently shown that the routing directly impacts the results of the network lifetime maximization process. Indeed, we have analyzed the behavior of several routing protocols in WMSN and the obtained results highlighted this influence. We have therefore proposed an analytic model integrating simultaneously the encoding of data at the source nodes and their routing to the base station. We have developed a semi-distributed resolution of this problem. The results obtained were very encouraging.Thus, in the second part, a fully distributed solution was proposed, in which, the routing axis cannot be achieved without the parameters, that should be determined and updated by the data processing axis. On the other hand, the data processing axis cannot be achieved without the routing tables updated by the routing axis. The proposed solution allows: a) an end-to-end routing with local decisions at each video sensor node and b) the choose of the sufficient number of paths needed to ensure a reliable data transmission.For the rest, we have completed our work by considering more realistic constraints, in particular the dynamic reliability of the links as well as the variation of their capacities (according to the remaining energy of the intermediate nodes). The simulation results showed savings of around 25% of the total energy
Libros sobre el tema "Multimedia Optimization"
Karri, Ramesh y David Goodman, eds. System-Level Power Optimization for Wireless Multimedia Communication. Boston: Kluwer Academic Publishers, 2002. http://dx.doi.org/10.1007/b117504.
Texto completoVirtanen, Seppo. Adoption and optimization of embedded and real-time communication systems. Hershey, PA: Information Science Reference, 2013.
Buscar texto completoRamesh, Karri y Goodman David J. 1939-, eds. System-level power optimization for wireless multimedia communication: Power aware computing. Boston: Kluwer Academic, 2002.
Buscar texto completoVideo and multimedia transmissions over cellular networks: Analysis, modeling, and optimization in live 3G mobile networks. Chichester, West Sussex, U.K: Wiley, 2009.
Buscar texto completoSoong, Kim Che, Melikov Agassi y SpringerLink (Online service), eds. Performance Analysis and Optimization of Multi-Traffic on Communication Networks. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.
Buscar texto completoGoodman, David J. y Ramesh Karri. System Level Power Optimization for Wireless Multimedia Communication: Power Aware Computing. Kap/Boston (E), 2002.
Buscar texto completoSystem-Level Power Optimization for Wireless Multimedia Communication: Power Aware Computing. Springer, 2002.
Buscar texto completoGoodman, David y Ramesh Karri. System-Level Power Optimization for Wireless Multimedia Communication: Power Aware Computing. Springer, 2013.
Buscar texto completoGoodman, David y Ramesh Karri. System-Level Power Optimization for Wireless Multimedia Communication: Power Aware Computing. Springer, 2013.
Buscar texto completoShah, Mubarak y Omar Oreifej. Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications. Springer, 2016.
Buscar texto completoCapítulos de libros sobre el tema "Multimedia Optimization"
Yang, Gang y Xirong Li. "Classifier Belief Optimization for Visual Categorization". En MultiMedia Modeling, 567–79. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67832-6_46.
Texto completoChannappayya, Sumohana y Alan C. Bovik. "Structural Similarity Index Based Optimization". En Encyclopedia of Multimedia, 832–36. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_67.
Texto completoPiatrik, Tomas y Ebroul Izquierdo. "Image Classification Using an Ant Colony Optimization Approach". En Semantic Multimedia, 159–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11930334_13.
Texto completoFang, Chengfang, Chunwang Zhang y Ee-Chien Chang. "An Optimization Model for Aesthetic Two-Dimensional Barcodes". En MultiMedia Modeling, 278–90. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04114-8_24.
Texto completoYao, Peng, Hua Zhang, Yanbing Xue y Shengyong Chen. "AGO: Accelerating Global Optimization for Accurate Stereo Matching". En MultiMedia Modeling, 67–80. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73603-7_6.
Texto completoKofler, Ingo, Christian Timmerer y Hermann Hellwagner. "Optimization-Based Multimedia Adaptation Decision-Taking". En Encyclopedia of Multimedia, 699–704. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_59.
Texto completoYe, Mang, Jun Chen, Qingming Leng, Chao Liang, Zheng Wang y Kaimin Sun. "Coupled-View Based Ranking Optimization for Person Re-identification". En MultiMedia Modeling, 105–17. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14445-0_10.
Texto completoChen, Fangdong y Houqiang Li. "Improved Rate-Distortion Optimization Algorithms for HEVC Lossless Coding". En MultiMedia Modeling, 454–65. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14445-0_39.
Texto completoSheng, Zhe, Dajiang Zhou, Heming Sun y Satoshi Goto. "Low-Complexity Rate-Distortion Optimization Algorithms for HEVC Intra Prediction". En MultiMedia Modeling, 541–52. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04114-8_46.
Texto completoUrruty, Thierry, Fatima Belkouch, Chabane Djeraba, Edouard Gerard, Jean de Bissy, Olivier Lombard y Patrick Alleaume. "Optimization of Video Content Descriptions for Retrieval". En Encyclopedia of Multimedia, 698. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_171.
Texto completoActas de conferencias sobre el tema "Multimedia Optimization"
Mancas, Catalina y Mihai Mocanu. "QoS optimization in congested multimedia networks". En 2013 36th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2013. http://dx.doi.org/10.1109/tsp.2013.6613887.
Texto completoChang, Seok-Ho, Jihwan P. Choi, Pamela C. Cosman y Laurence B. Milstein. "Scalable multimedia optimization in MIMO systems". En MILCOM 2015 - 2015 IEEE Military Communications Conference. IEEE, 2015. http://dx.doi.org/10.1109/milcom.2015.7357433.
Texto completoBarreto, Priscila Solis y Paulo H. P. de Carvalho. "Network Planning Optimization for Multimedia Networks". En 2008 7th IEEE International Symposium on Network Computing and Applications (NCA). IEEE, 2008. http://dx.doi.org/10.1109/nca.2008.30.
Texto completoHuang, Jianwei. "Session details: Multimedia over wireless symposium: collaborative and optimization for multimedia". En IWCMC07: International Wireless Communications and Mobile Computing Conference. New York, NY, USA: ACM, 2007. http://dx.doi.org/10.1145/3259077.
Texto completoRazaque, Abdul, Sai Subramanya Vamsi Chavali, Sundeep Goud Malkapuram, Satya Siva Varma Nadimpalli, Suharsha Vommina, Dinesh Kumar Atukuri y Vamsee Sai Malllapu. "Trans receiving multimedia using Raspberry-Pi". En 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7755019.
Texto completoRui, Liu, Yan Danfeng, Lin Fan y Yang Fangchun. "Optimization of hierarchical vulnerability assessment method". En Multimedia Technology (IC-BNMT). IEEE, 2009. http://dx.doi.org/10.1109/icbnmt.2009.5348535.
Texto completoSafadi, Bahjat y Georges Quenot. "Descriptor optimization for multimedia indexing and retrieval". En 2013 11th International Workshop on Content-Based Multimedia Indexing (CBMI). IEEE, 2013. http://dx.doi.org/10.1109/cbmi.2013.6576554.
Texto completoCao, Yu, Steven D. Blostein y Wai-Yip Chan. "Optimization of rateless-coded asynchronous multimedia multicast". En 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC 2011). IEEE, 2011. http://dx.doi.org/10.1109/pimrc.2011.6139888.
Texto completoGao, Sheng y Qibin Sun. "Classifier Optimization for Multimedia Semantic Concept Detection". En 2006 IEEE International Conference on Multimedia and Expo. IEEE, 2006. http://dx.doi.org/10.1109/icme.2006.262824.
Texto completoJing, Sun y Sun Yafei. "Optimization Electrical Engineering Teaching Utilize Multimedia Courseware". En 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.234.
Texto completo