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Статті в журналах з теми "Retrieval systems"
Tokumi, Yuta, Junki Hakamata, and Masataka Tokumaru. "Development of a Nutritional Management System for a Healthy Eating Habits Support System." Journal of Advanced Computational Intelligence and Intelligent Informatics 17, no. 2 (March 20, 2013): 324–34. http://dx.doi.org/10.20965/jaciii.2013.p0324.
Повний текст джерелаCrook, D. A., B. J. Adair, and L. J. Hetherington. "Low-cost device for retrieval of moorings deployed with underwater remote release systems." Marine and Freshwater Research 69, no. 3 (2018): 473. http://dx.doi.org/10.1071/mf17189.
Повний текст джерелаOrscheschek, Franziska, Tilo Strobach, Torsten Schubert, and Timothy Rickard. "Two retrievals from a single cue: A bottleneck persists across episodic and semantic memory." Quarterly Journal of Experimental Psychology 72, no. 5 (May 28, 2018): 1005–28. http://dx.doi.org/10.1177/1747021818776818.
Повний текст джерелаAbubacker, K. A. Shaheer, J. Sutha, and K. A. Shahul Hameed. "A simple multi-feature based stereoscopic medical image retrieval system." Polish Journal of Medical Physics and Engineering 25, no. 2 (June 1, 2019): 127–30. http://dx.doi.org/10.2478/pjmpe-2019-0017.
Повний текст джерелаLuo, Youmeng, Wei Li, Xiaoyu Ma, and Kaiqiang Zhang. "Image Retrieval Algorithm Based on Locality-Sensitive Hash Using Convolutional Neural Network and Attention Mechanism." Information 13, no. 10 (September 24, 2022): 446. http://dx.doi.org/10.3390/info13100446.
Повний текст джерелаTseng, Chien-Hao, Chia-Chien Hsieh, Dah-Jing Jwo, Jyh-Horng Wu, Ruey-Kai Sheu, and Lun-Chi Chen. "Person Retrieval in Video Surveillance Using Deep Learning–Based Instance Segmentation." Journal of Sensors 2021 (August 21, 2021): 1–12. http://dx.doi.org/10.1155/2021/9566628.
Повний текст джерелаD, Lande, Soboliev A, and Dmytrenko O. "Intelligent technologies in information retrieval systems." Artificial Intelligence 27, jai2022.27(1) (June 20, 2022): 260–68. http://dx.doi.org/10.15407/jai2022.01.260.
Повний текст джерелаS, Sangeetha, and Srividhya S.R. "Deconstructing Information Retrieval Systems with Plumbara." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 868–74. http://dx.doi.org/10.5373/jardcs/v11/20192645.
Повний текст джерелаDr. V. Suma. "A Novel Information retrieval system for distributed cloud using Hybrid Deep Fuzzy Hashing Algorithm." September 2020 02, no. 03 (August 28, 2020): 151–60. http://dx.doi.org/10.36548/jitdw.2020.3.003.
Повний текст джерелаEnser, P. G. B. "Document retrieval systems." International Journal of Information Management 10, no. 2 (June 1990): 156–57. http://dx.doi.org/10.1016/0268-4012(90)90009-h.
Повний текст джерелаДисертації з теми "Retrieval systems"
Mills, Timothy J. "Content modelling in multimedia information retrieval systems : the Cobra retrieval system." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442405.
Повний текст джерелаAl-Maskari, Azzah. "Evaluation of interactive information retrieval systems." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538079.
Повний текст джерелаZhang, Dengsheng 1963. "Image retrieval based on shape." Monash University, School of Computing and Information Technology, 2002. http://arrow.monash.edu.au/hdl/1959.1/8688.
Повний текст джерелаRomano, Nicholas C., Dmitri G. Roussinov, Jay F. Nunamaker, and Hsinchun Chen. "Collaborative Information Retrieval Environment: Integration of Information Retrieval with Group Support Systems." HICSS, 1999. http://hdl.handle.net/10150/105688.
Повний текст джерелаObservations of Information Retrieval (IR) system user experiences reveal a strong desire for collaborative search while at the same time suggesting that collaborative capabilities are rarely, and then only in a limited fashion, supported by current searching and visualization tools. Equally interesting is the fact that observations of user experiences with Group Support Systems (GSS) reveal that although access to external information and the ability to search for relevant material is often vital to the progress of GSS sessions, integrated support for collaborative searching and visualization of results is lacking in GSS systems. After reviewing both user experiences described in IR and GSS literature and observing and interviewing users of existing IR and GSS commercial and prototype systems, the authors conclude that there is an obvious demand for systems supporting multi-user IR.. It is surprising to the authors that very little attention has been given to the common ground shared by these two important research domains. With this in mind, our paper describes how user experiences with IR and GSS systems has shed light on a promising new area of collaborative research and led to the development of a prototype that merges the two paradigms into a Collaborative Information Retrieval Environment (CIRE). Finally the paper presents theory developed from initial user experiences with our prototype and describes plans to test the efficacy of this new paradigm empirically through controlled experimentation.
Xie, Jinsheng. "On the analysis of selected automated storage and retrieval systems." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/25020.
Повний текст джерелаWatkins, Alfred R. "Continuous media object modeling, storage, and retrieval." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/9184.
Повний текст джерелаPortabella, Arnús Marcos. "Wind Field Retrieval from Satellite Radar Systems." Doctoral thesis, Universitat de Barcelona, 2002. http://hdl.handle.net/10803/734.
Повний текст джерелаIn order to invert the geophysical model function (GMF), which relates the radar backscatter measurement with the wind speed and direction (unknowns), two independent measurements over the same scene (wind cell) are at least needed. The degree of independence of such measurements is given by the azimuth (view) angle separation among them. This thesis is focused on improving the wind retrieval for determined systems (two or more measurements) with poor azimuth diversity and for underdetermined systems (one single measurement). For such purpose, observations from two different radar systems, i.e., SeaWinds and SAR (Synthetic Aperture Radar), are used.
The wind retrieval methods proposed in this book for determined (Multiple Solution Scheme, denoted MSS) and underdetermined (SAR Wind Retrieval Algorithm, denoted SWRA) systems are based on Bayesian methodology, that is, on maximizing the probability of obtaining the "true" wind given the radar measurements and the a priori wind information (often provided by numerical weather prediction models), assuming that all wind information sources contain errors. In contrast with the standard procedure for determined systems, the MSS fully uses the information obtained from inversion, which turns out to positively impact the wind retrieval when poor azimuth diversity. On the other hand, in contrast with the various algorithms used nowadays to resolve the wind vector for underdetermined systems, the SWRA assumes not only that the system can not be solved without additional information (underdetermination assumption) but also that both the algorithms and the additional information (which are combined to retrieved the wind vector) contain errors and these should be well characterized. The MSS and the SWRA give promising results, improving the wind retrieval quality as compared to the methods used up to now.
Finally, a generic quality control is proposed for determined systems. In general, high-quality retrieved wind fields can be obtained from scatterometer (determined systems) measurements. However, geophysical conditions other than wind (e.g., rain, confused sea state or sea ice) can distort the radar signal and, in turn, substantially decrease the wind retrieval quality. The quality control method uses the inversion residual (which is sensitive to inconsistencies between observations and the geophysical model function that are mainly produced when conditions other than wind dominate the radar backscatter signal) to detect and reject the poor-quality retrievals. The method gives good results, minimizing the rejection of good-quality data and maximizing the rejection of poor-quality data, including rain contamination.
Engström, Felix, and Eli Pleaner. "Learning Methods for Improving News Retrieval Systems." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187492.
Повний текст джерелаFöretag som tillhandahåller innehållshanteringstjänster be- höver effektiva och precisa metoder för att med minsta möjliga mänskliga arbetskraft utvinna relevant innehåll ur stora mängder data. Ett exempel på detta är tjänster för insamlande av nyheter, där nyheter skall utvinnas från olika källor. Som en del av den processen krävs att de kan avgöra om en text är en nyhetsartikel eller någon annan form av text. Skillnaden mellan en nyhetsartikel och en text skriven för en blogg kan vara subtil, men är avgörande för dessa företag. Denna rapport utforskar formatklassifi- cering: uppgiften att klassificera texter baserat på vilket format de är skrivna för. Exempel på format är: nyhet- sartikel, bloggtext eller forumtext. Mer specifikt tar den sig an uppgiften att undersöka hur väl de metoder som idag används i den väl utforskade uppgiften att klassificera texter baserat på ämne fungerar applicerade på formatk- lassificering. Det utforskas med experimentell evaluering på ett nytt dataset som konstruerats genom att kombin- era ett flertal existerande dataset. Detta görs både som en binär- och multiklassificeringsuppgift i en bag-of-word vektorrymd. Ett antal ämnesklassificeringsmetoder väljs baserat på resultat från tidigare forskning, och hur dessa presterar på formatklassificering undersöks. Vi drar slut- satsen att våra resultat visar att de textklassificeringsme- toder vi testat fungerar acceptabelt väl på formatklassifi- cering. Vi föreslår vidare gradient-boost eller multinomial naive bayes för att lösa uppgiften, beroende på om fokus ligger på kvaliteten av klassificeringen eller prestanda. Slut- ligen diskuteras resultaten , de sätts i relation till de begrän- sningar som förelegat och förslag till framtida forskning ges.
Liu, Chi-Cheng. "Implementation of parallel intelligent information retrieval systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq30509.pdf.
Повний текст джерелаTang, Wai-hung, and 鄧偉雄. "An anonymity scheme for file retrieval systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40887972.
Повний текст джерелаКниги з теми "Retrieval systems"
Gallery, Art Alive, ed. Retrieval systems. New Delhi: Art Alive Gallery, 2009.
Знайти повний текст джерела1953-, Willett Peter, ed. Document retrieval systems. London: Taylor Graham, 1988.
Знайти повний текст джерелаHeikkila, Ralph C. Election signature retrieval systems. Washington, D.C: National Clearinghouse on Election Administration, Federal Election Commission, 1992.
Знайти повний текст джерелаText information retrieval systems. San Diego: Academic Press, 1992.
Знайти повний текст джерелаT, Meadow Charles, Boyce Bert R, and Kraft Donald H, eds. Text information retrieval systems. 3rd ed. Amsterdam: Academic, 2007.
Знайти повний текст джерелаR, Boyce Bert, and Kraft Donald H, eds. Text information retrieval systems. 2nd ed. San Diego: Academic Press, 2000.
Знайти повний текст джерелаMultimedia information retrieval. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2010.
Знайти повний текст джерелаKowalski, Gerald J., and Mark T. Maybury. Information Storage and Retrieval Systems. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/b116174.
Повний текст джерелаJ, Warner Amy, and Lancaster F. Wilfrid 1933-, eds. Information retrieval today. Arlington, Va: Information Resources Press, 1993.
Знайти повний текст джерелаF, Smeaton Alan, ed. Information Retrieval and Hypertext. Boston, MA: Springer US, 1996.
Знайти повний текст джерелаЧастини книг з теми "Retrieval systems"
Hiemstra, Djoerd, and Wessel Kraaij. "Evaluation of Multimedia Retrieval Systems." In Multimedia Retrieval, 347–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72895-5_13.
Повний текст джерелаHersh, William R., William M. Detmer, and Mark E. Frisse. "Information-Retrieval Systems." In Medical Informatics, 539–72. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-0-387-21721-5_15.
Повний текст джерелаLalmas, Mounia, and Andrew Trotman. "XML Retrieval." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_474-2.
Повний текст джерелаBalog, Krisztian. "Entity Retrieval." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_80724-1.
Повний текст джерелаAmati, Giambattista. "Information Retrieval." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_915-2.
Повний текст джерелаLalmas, Mounia, and Andrew Trotman. "XML Retrieval." In Encyclopedia of Database Systems, 3616–21. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_474.
Повний текст джерелаAmati, Giambattista. "Information Retrieval." In Encyclopedia of Database Systems, 1519–23. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_915.
Повний текст джерелаAli-Ahmed, Syed Toufeeq. "Information Retrieval." In Encyclopedia of Systems Biology, 1026. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_153.
Повний текст джерелаLalmas, Mounia, and Andrew Trotman. "XML Retrieval." In Encyclopedia of Database Systems, 4784–89. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_474.
Повний текст джерелаBalog, Krisztian. "Entity Retrieval." In Encyclopedia of Database Systems, 1326–31. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_80724.
Повний текст джерелаТези доповідей конференцій з теми "Retrieval systems"
Song, Yiping, Cheng-Te Li, Jian-Yun Nie, Ming Zhang, Dongyan Zhao, and Rui Yan. "An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/609.
Повний текст джерелаLiang, Yan, Wen Feng Lu, Ying Liu, and Soon Chong Johnson Lim. "Interactive Interface Design for Design Rationale Search and Retrieval." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28392.
Повний текст джерелаChan, Yi Meng, Richard T. Harvey, and Dan Smith. "Building systems to block pornography." In Challenge of Image Retrieval. BCS Learning & Development, 1999. http://dx.doi.org/10.14236/ewic/cir1999.8.
Повний текст джерелаZhang, Guoxian, and Devendra P. Garg. "Mobile Multi-Robot Control in Target Search and Retrieval." In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2196.
Повний текст джерелаMulhem, P., and L. Nigay. "Interactive information retrieval systems." In the 19th annual international ACM SIGIR conference. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/243199.243280.
Повний текст джерелаMi Hee, Yoon Yong Ik, and Kio Chung Kim. "Unified video retrieval system supporting similarity retrieval." In Proceedings. Tenth International Workshop on Database and Expert Systems Applications. DEXA 99. IEEE, 1999. http://dx.doi.org/10.1109/dexa.1999.795298.
Повний текст джерелаAlwis, Sujeewa, and Jim Austin. "A Novel Architecture for Trademark Image Retrieval Systems." In Challenge of Image Retrieval. BCS Learning & Development, 1998. http://dx.doi.org/10.14236/ewic/cir1998.10.
Повний текст джерелаMorris, Elissa, and Daniel A. McAdams. "Bioinspired Origami: Case Studies Using a Keyword Search Algorithm." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22228.
Повний текст джерелаXiao, Jinjiang, Mulad Winaro, Mohammas Eissa, and Akram Mahmoud. "Overcoming Deployment and Retrieval Challenges with Killed Well Cable Deployed Electric Submersible Pump Systems – Lessons Learned from Five Years of CDESP History." In SPE Eastern Europe Subsurface Conference. SPE, 2021. http://dx.doi.org/10.2118/208551-ms.
Повний текст джерелаXu, Junling, Baowen Xu, and Shuaiqiu Men. "Feature-Based Similarity Retrieval in Content-Based Image Retrieval." In 2010 7th Web Information Systems and Applications Conference (WISA). IEEE, 2010. http://dx.doi.org/10.1109/wisa.2010.46.
Повний текст джерелаЗвіти організацій з теми "Retrieval systems"
RIECK, C. A. Project W-211, initial tank retrieval systems, retrieval control system software configuration management plan. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/781535.
Повний текст джерелаBaylor, Robert. Automated information retrieval systems for legal research. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.648.
Повний текст джерелаRieck, C. A. Engineer/constructor description of work for Tank 241-SY-102 retrieval system, project W-211, initial tank retrieval systems. Office of Scientific and Technical Information (OSTI), February 1996. http://dx.doi.org/10.2172/483376.
Повний текст джерелаBitz, D. A., D. L. Berry, and L. J. Jardine. Decision and systems analysis for underground storage tank waste retrieval systems and tank waste remediation system. Office of Scientific and Technical Information (OSTI), March 1994. http://dx.doi.org/10.2172/10196816.
Повний текст джерелаBerry, D. L., and L. J. Jardine. Decision and systems analysis for underground storage tank waste retrieval systems and tank waste remediation system. Office of Scientific and Technical Information (OSTI), October 1993. http://dx.doi.org/10.2172/10133252.
Повний текст джерелаRIECK, C. A. System Engineering Management and implementation plan for Project W-211, ''Initial tank retrieval systems''. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/781523.
Повний текст джерелаHuckfeldt, R. A. Preliminary fire hazards analysis for W-211, Initial Tank Retrieval Systems. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/34338.
Повний текст джерелаLEONARD, M. W., and G. A. HOFFERBER. Systems Engineering Implementation Plan for Single Shell Tanks (SST) Retrieval Projects. Office of Scientific and Technical Information (OSTI), November 2000. http://dx.doi.org/10.2172/805455.
Повний текст джерелаVAN BEEK, J. E. System Engineering Management and Implementation Plan for Project W-211 Initial Tank Retrieval Systems (ITRS). Office of Scientific and Technical Information (OSTI), May 2000. http://dx.doi.org/10.2172/803633.
Повний текст джерелаVAN BEEK, J. E. Project Execution Plan for Project W-211 Initial Tank Retrieval Systems (ITRS). Office of Scientific and Technical Information (OSTI), September 1999. http://dx.doi.org/10.2172/798001.
Повний текст джерела