Academic literature on the topic 'Information extraction and fusion'
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Journal articles on the topic "Information extraction and fusion"
Yang, Zhongguo, Mingzhu Zhang, Zhongmei Zhang, Han Li, Chen Liu, and Sikandar Ali. "Lecture Information Service Based on Multiple Features Fusion." International Journal of Software Engineering and Knowledge Engineering 31, no. 04 (April 2021): 545–62. http://dx.doi.org/10.1142/s0218194021400076.
Full textZhang, Xin, Li Yang, and Yan Zhang. "Multi-Source Information Fusion Based on Data Driven." Applied Mechanics and Materials 40-41 (November 2010): 121–26. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.121.
Full textLiu, Xia, Zhijing Xu, and Kan Huang. "Multimodal Emotion Recognition Based on Cascaded Multichannel and Hierarchical Fusion." Computational Intelligence and Neuroscience 2023 (January 5, 2023): 1–18. http://dx.doi.org/10.1155/2023/9645611.
Full textDeren, LI, and SHAO Juliang. "HOUSE EXTRACTION WITH MULTIRESOLUTION ANALYSIS AND INFORMATION FUSION." Geo-spatial Information Science 1, no. 1 (October 1998): 6–12. http://dx.doi.org/10.1080/10095020.1998.10553277.
Full textLiu, Tingting, Jian Yin, and Qingfeng Qin. "MFHE: Multi-View Fusion-Based Heterogeneous Information Network Embedding." Applied Sciences 12, no. 16 (August 17, 2022): 8218. http://dx.doi.org/10.3390/app12168218.
Full textHan, Yan Bin, Geng Shi Zhang, and Jin Ping Li. "A Feature Extraction Strategy Based on Multiple Color Information." Advanced Materials Research 433-440 (January 2012): 6175–81. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.6175.
Full textWang, Wenya, and Sinno Jialin Pan. "Integrating Deep Learning with Logic Fusion for Information Extraction." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 9225–32. http://dx.doi.org/10.1609/aaai.v34i05.6460.
Full textZhao, Jiang, Jiao Wang, and Meng Shang. "Fault Diagnosis Method of Time Domain and Time-Frequency Domain Based on Information Fusion." Applied Mechanics and Materials 300-301 (February 2013): 635–39. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.635.
Full textYan, Zhiqiang, Hongyuan Wang, Qianhao Ning, and Yinxi Lu. "Robust Image Matching Based on Image Feature and Depth Information Fusion." Machines 10, no. 6 (June 8, 2022): 456. http://dx.doi.org/10.3390/machines10060456.
Full textZhu, Danyao, Luhe Wan, and Wei Gao. "Fusion Method Evaluation and Classification Suitability Study of Wetland Satellite Imagery." Earth Sciences Research Journal 23, no. 4 (October 1, 2019): 339–46. http://dx.doi.org/10.15446/esrj.v23n4.84350.
Full textDissertations / Theses on the topic "Information extraction and fusion"
Ahmad, Muhammad Imran. "Feature extraction and information fusion in face and palmprint multimodal biometrics." Thesis, University of Newcastle upon Tyne, 2013. http://hdl.handle.net/10443/2128.
Full textJin, Xiaoying. "Automatic extraction of man-made objects from high-resolution satellite imagery by information fusion." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/5816.
Full textThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (November 15, 2006) Vita. Includes bibliographical references.
Arif-Uz-Zaman, Kazi. "Failure and maintenance information extraction methodology using multiple databases from industry: A new data fusion approach." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/116354/1/Kazi_Arif-Uz-Zaman_Thesis.pdf.
Full textThuillier, Etienne. "Extraction of mobility information through heterogeneous data fusion : a multi-source, multi-scale, and multi-modal problem." Thesis, Bourgogne Franche-Comté, 2017. http://www.theses.fr/2017UBFCA019.
Full textToday it is a fact that we live in a world where ecological, economic and societal issues are increasingly pressing. At the crossroads of the various guidelines envisaged to address these problems, a more accurate vision of human mobility is a central and major axis, which has repercussions on all related fields such as transport, social sciences, urban planning, management policies, ecology, etc. It is also in the context of strong budgetary constraints that the main actors of mobility on the territories seek to rationalize the transport services and the movements of individuals. Human mobility is therefore a strategic challenge both for local communities and for users, which must be observed, understood and anticipated.This study of mobility is based above all on a precise observation of the movements of users on the territories. Nowadays mobility operators are mainly focusing on the massive use of user data. The simultaneous use of multi-source, multi-modal, and multi-scale data opens many possibilities, but the latter presents major technological and scientific challenges. The mobility models presented in the literature are too often focused on limited experimental areas, using calibrated data, etc., and their application in real contexts and on a larger scale is therefore questionable. We thus identify two major issues that enable us to meet this need for a better knowledge of human mobility, but also to a better application of this knowledge. The first issue concerns the extraction of mobility information from heterogeneous data fusion. The second problem concerns the relevance of this fusion in a real context, and on a larger scale. These issues are addressed in this dissertation: the first, through two data fusion models that allow the extraction of mobility information, the second through the application of these fusion models within the ANR Norm-Atis project.In this thesis, we finally follow the development of a whole chain of processes. Starting with a study of human mobility, and then mobility models, we present two data fusion models, and we analyze their relevance in a concrete case. The first model we propose allows to extract 12 types of mobility behaviors. It is based on an unsupervised learning of mobile phone data. We validate our results using official data from the INSEE, and we infer from our results, dynamic behaviors that can not be observed through traditional mobility data. This is a strong added-value of our model. The second model operates a mobility flows decompositoin into six mobility purposes. It is based on a supervised learning of mobility surveys data and static data from the land use. This model is then applied to the aggregated data within the Norm-Atis project. The computing times are sufficiently powerful to allow an application of this model in a real-time context
Foucard, Rémi. "Fusion multi-niveaux par boosting pour le tagging automatique." Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0093/document.
Full textTags constitute a very useful tool for multimedia document indexing. This PhD thesis deals with automatic tagging, which consists in associating a set of tags to each song automatically, using an algorithm. We use boosting techniques to design a learning which better considers the complexity of the information expressed by music. A boosting algorithm is proposed, which can jointly use song descriptions associated to excerpts of different durations. This algorithm is used to fuse new descriptions, which belong to different abstraction levels. Finally, a new learning framework is proposed for automatic tagging, which better leverages the subtlety ofthe information expressed by music
Gulen, Elvan. "Fusing Semantic Information Extracted From Visual, Auditory And Textual Data Of Videos." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614582/index.pdf.
Full textanalyzing and uniting the semantic information that is extracted from multimodal data by utilizing concept interactions and consequently generating a semantic dataset which is ready to be stored in a database. Besides, experiments are conducted to compare results obtained from the proposed multimodal fusion operation with results obtained as an outcome of semantic information extraction from just one modality and other fusion methods. The results indicate that fusing all available information along with concept relations yields better results than any unimodal approaches and other traditional fusion methods in overall.
Muhammad, Hanif Shehzad. "Feature selection and classifier combination: Application to the extraction of textual information in scene images." Paris 6, 2009. http://www.theses.fr/2009PA066521.
Full textSkibinski, Sebastian [Verfasser], Heinrich [Akademischer Betreuer] Müller, and Uwe [Gutachter] Schwiegelshohn. "Extraction, localization, and fusion of collective vehicle data / Sebastian Skibinski ; Gutachter: Uwe Schwiegelshohn ; Betreuer: Heinrich Müller." Dortmund : Universitätsbibliothek Dortmund, 2019. http://d-nb.info/1191990192/34.
Full textSkibinski, Sebastian [Verfasser], Heinrich Akademischer Betreuer] Müller, and Uwe [Gutachter] [Schwiegelshohn. "Extraction, localization, and fusion of collective vehicle data / Sebastian Skibinski ; Gutachter: Uwe Schwiegelshohn ; Betreuer: Heinrich Müller." Dortmund : Universitätsbibliothek Dortmund, 2019. http://d-nb.info/1191990192/34.
Full textApatean, Anca Ioana. "Contributions à la fusion des informations : application à la reconnaissance des obstacles dans les images visible et infrarouge." Phd thesis, INSA de Rouen, 2010. http://tel.archives-ouvertes.fr/tel-00621202.
Full textBooks on the topic "Information extraction and fusion"
Martin, Golz, Kuh Anthony, Obradovic Dragan, Tanaka Toshihisa, and SpringerLink (Online service), eds. Signal Processing Techniques for Knowledge Extraction and Information Fusion. Boston, MA: Springer Science+Business Media, LLC, 2008.
Find full textMandic, Danilo, Martin Golz, Anthony Kuh, Dragan Obradovic, and Toshihisa Tanaka, eds. Signal Processing Techniques for Knowledge Extraction and Information Fusion. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7.
Full textPazienza, Maria Teresa, ed. Information Extraction. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48089-7.
Full textLi, Jinxing, Bob Zhang, and David Zhang. Information Fusion. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8976-5.
Full textMaybury, Mark T., ed. Multimedia Information Extraction. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118219546.
Full textPaolo, Coletti, ed. Information extraction in finance. Southampton: WIT Press, 2008.
Find full textPopovich, Vasily V., Christophe Claramunt, Manfred Schrenk, and Kyrill V. Korolenko, eds. Information Fusion and Geographic Information Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00304-2.
Full textPopovich, Vasily V., Christophe Claramunt, Thomas Devogele, Manfred Schrenk, and Kyrill Korolenko, eds. Information Fusion and Geographic Information Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19766-6.
Full textPopovich, Vasily V., Manfred Schrenk, and Kyrill V. Korolenko, eds. Information Fusion and Geographic Information Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-37629-3.
Full textM, Jordan John, ed. Human-centered information fusion. Boston: Artech House, 2010.
Find full textBook chapters on the topic "Information extraction and fusion"
Baki Ermis, Erhan, Venkatesh Saligrama, and Pierre-marc Jodoin. "Information Fusion and Anomaly Detection with Uncalibrated Cameras in Video Surveillance." In Multimedia Information Extraction, 201–16. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118219546.ch13.
Full textZhao, Haitao, Zhihui Lai, Henry Leung, and Xianyi Zhang. "Latent Semantic Feature Extraction." In Information Fusion and Data Science, 13–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40794-0_2.
Full textZhao, Haitao, Zhihui Lai, Henry Leung, and Xianyi Zhang. "Manifold-Learning-Based Feature Extraction." In Information Fusion and Data Science, 53–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40794-0_4.
Full textXuejun, Wang, Zhao Linlin, and Wang Shuang. "A Fusion Scheme of Video Object Extraction." In Recent Advances in Computer Science and Information Engineering, 251–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25792-6_38.
Full textMandic, Danilo, George Souretis, Wai Yie Leong, David Looney, Marc M. Van Hulle, and Toshihisa Tanaka. "Complex Empirical Mode Decomposition for Multichannel Information Fusion." In Signal Processing Techniques for Knowledge Extraction and Information Fusion, 243–60. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7_13.
Full textObradovic, Dragan, Henning Lenz, Markus Schupfner, and Kai Heesche. "Multimodal Fusion for Car Navigation Systems." In Signal Processing Techniques for Knowledge Extraction and Information Fusion, 141–58. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7_8.
Full textCalhoun, Vince D., and Tülay Adali. "ICA for Fusion of Brain Imaging Data." In Signal Processing Techniques for Knowledge Extraction and Information Fusion, 221–40. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7_12.
Full textChen, Zuocong. "Method for Extraction and Fusion Based on KL Measure." In Communications in Computer and Information Science, 42–51. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0118-0_4.
Full textJelfs, Beth, Phebe Vayanos, Soroush Javidi, Vanessa Su Lee Goh, and Danilo Mandic. "Collaborative Adaptive Filters for Online Knowledge Extraction and Information Fusion." In Signal Processing Techniques for Knowledge Extraction and Information Fusion, 3–21. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7_1.
Full textRutkowski, Tomasz M., Andrzej Cichocki, and Danilo Mandic. "Information Fusion for Perceptual Feedback: A Brain Activity Sonification Approach." In Signal Processing Techniques for Knowledge Extraction and Information Fusion, 261–73. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7_14.
Full textConference papers on the topic "Information extraction and fusion"
Forsling, Robin, Zoran Sjanic, Fredrik Gustafsson, and Gustaf Hendeby. "Communication Efficient Decentralized Track Fusion Using Selective Information Extraction." In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE, 2020. http://dx.doi.org/10.23919/fusion45008.2020.9190575.
Full textLiu, Tsa Chun, Ratnasingham Tharmarasa, Simon Halle, Mihai Florea, Mike McDonald, and Thia Kirubarajan. "Anomaly Detection with Pattern of Life Extraction for GMTI Tracking." In 2019 22th International Conference on Information Fusion (FUSION). IEEE, 2019. http://dx.doi.org/10.23919/fusion43075.2019.9011442.
Full textXiaoxi Yan, Chongzhao Han, and Jing Liu. "State extraction of probability hypothesis density filter based on Dirichlet distribution." In 2010 13th International Conference on Information Fusion (FUSION 2010). IEEE, 2010. http://dx.doi.org/10.1109/icif.2010.5711955.
Full textDatta, S., B. R. Choudhuri, and A. Ganguli. "Text extraction system." In Proceedings of the Sixth International Conference of Information Fusion. IEEE, 2003. http://dx.doi.org/10.1109/icif.2003.177409.
Full textLilienthal, Jannis, and Waltenegus Dargie. "Extraction of Motion Artifacts from the Measurements of a Wireless Electrocardiogram using Tensor Decomposition." In 2019 22th International Conference on Information Fusion (FUSION). IEEE, 2019. http://dx.doi.org/10.23919/fusion43075.2019.9011290.
Full textSUWANDI, ADANG, and CATHERINE OLIVIA. "Knowledge Extraction for Infomation Fusion." In Fourth International Conference on Advances in Information Processing and Communication Technology - IPCT 2016. Institute of Research Engineers and Doctors, 2016. http://dx.doi.org/10.15224/978-1-63248-099-6-32.
Full textUlmke, M., and W. Koch. "Road Map Extraction using GMTI Tracking." In 2006 9th International Conference on Information Fusion. IEEE, 2006. http://dx.doi.org/10.1109/icif.2006.301564.
Full textSUWANDI, ADANG, and ARWIN DATUMAYA. "Information Fusion as Knowledge Extraction in an Information Processing System." In Fourth International Conference on Advances in Computing, Electronics and Communication - ACEC 2016. Institute of Research Engineers and Doctors, 2016. http://dx.doi.org/10.15224/978-1-63248-113-9-05.
Full textZuobin, Wu, Mao Kezhi, and Gee-Wah Ng. "Feature Regrouping for CCA - Based Feature Fusion and Extraction Through Normalized Cut." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455397.
Full textDou, Weibei, Qingmin Liao, Su Ruan, Daniel Bloyet, Jean-Mac Constans, and Yanping Chen. "Automatic brain tumor extraction using fuzzy information fusion." In Second International Conference on Image and Graphics, edited by Wei Sui. SPIE, 2002. http://dx.doi.org/10.1117/12.477203.
Full textReports on the topic "Information extraction and fusion"
Etzioni, Oren. Open Information Extraction. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada538482.
Full textCohen, Eric, and Evelyne Tzoukermann. Phrase-based Multimedia Information Extraction. Fort Belvoir, VA: Defense Technical Information Center, July 2006. http://dx.doi.org/10.21236/ada456800.
Full textWhite, Michael, Tanya Korelsky, Claire Cardie, Vincent Ng, David Pierce, and Kiri Wagstaff. Multidocument Summarization via Information Extraction. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada457772.
Full textOnyshkevych, Boyan. Template Design for Information Extraction. Fort Belvoir, VA: Defense Technical Information Center, July 1993. http://dx.doi.org/10.21236/ada635849.
Full textSrihari, Rohini, and Wei Li. Information Extraction Supported Question Answering. Fort Belvoir, VA: Defense Technical Information Center, October 1999. http://dx.doi.org/10.21236/ada460042.
Full textShinyama, Yusuke, and Satoshi Sekine. Paraphrase Acquisition for Information Extraction. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada460236.
Full textIrwin, N. H., S. M. DeLand, and S. V. Crowder. Extraction of information from unstructured text. Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/148697.
Full textNurre, Joseph H. Automate Information Extraction from Scan Data. Fort Belvoir, VA: Defense Technical Information Center, November 1998. http://dx.doi.org/10.21236/ada362095.
Full textBray, O. H. Information integration for data fusion. Office of Scientific and Technical Information (OSTI), January 1997. http://dx.doi.org/10.2172/444047.
Full textCorkill, Daniel D. Collaborative Software for Information Fusion. Fort Belvoir, VA: Defense Technical Information Center, March 2005. http://dx.doi.org/10.21236/ada437538.
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