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Artykuły w czasopismach na temat "Localization density"
Gadre, Shridhar R., Sudhir A. Kulkarni i Rajeev K. Pathak. "Density‐based electron localization function via nonlocal density approximation". Journal of Chemical Physics 98, nr 4 (15.02.1993): 3574–76. http://dx.doi.org/10.1063/1.464082.
Pełny tekst źródłaMovaghar, B. "Localization and the density of states". Philosophical Magazine B 65, nr 5 (maj 1992): 1097–108. http://dx.doi.org/10.1080/13642819208217923.
Pełny tekst źródłaBalan, Radu, Peter G. Casazza, Christopher Heil i Zeph Landau. "Density, overcompleteness, and localization of frames". Electronic Research Announcements of the American Mathematical Society 12, nr 10 (7.07.2006): 71–86. http://dx.doi.org/10.1090/s1079-6762-06-00163-6.
Pełny tekst źródłaHutník, Ondrej, Egor A. Maximenko i Anna Mišková. "Toeplitz Localization Operators: Spectral Functions Density". Complex Analysis and Operator Theory 10, nr 8 (20.05.2016): 1757–74. http://dx.doi.org/10.1007/s11785-016-0564-1.
Pełny tekst źródłaPilmé, Julien. "Electron localization function from density components". Journal of Computational Chemistry 38, nr 4 (17.11.2016): 204–10. http://dx.doi.org/10.1002/jcc.24672.
Pełny tekst źródłaSchroer, Bert. "Area density of localization entropy: I. The case of wedge localization". Classical and Quantum Gravity 23, nr 17 (7.08.2006): 5227–48. http://dx.doi.org/10.1088/0264-9381/23/17/008.
Pełny tekst źródłaBouhdid, Badia, Wafa Akkari i Sofien Gannouni. "Low Cost Recursive Localization scheme for High Density Wireless Sensor Networks". International Journal on Semantic Web and Information Systems 13, nr 3 (lipiec 2017): 68–88. http://dx.doi.org/10.4018/ijswis.2017070104.
Pełny tekst źródłaSuslov, Igor' M. "Density of states near the localization threshold". Uspekhi Fizicheskih Nauk 166, nr 8 (1996): 907. http://dx.doi.org/10.3367/ufnr.0166.199608x.0907.
Pełny tekst źródłaMarsh, Richard J., Karin Pfisterer, Pauline Bennett, Liisa M. Hirvonen, Mathias Gautel, Gareth E. Jones i Susan Cox. "Artifact-free high-density localization microscopy analysis". Nature Methods 15, nr 9 (30.07.2018): 689–92. http://dx.doi.org/10.1038/s41592-018-0072-5.
Pełny tekst źródłaSuslov, Igor' M. "Density of states near the localization threshold". Physics-Uspekhi 39, nr 8 (31.08.1996): 848–49. http://dx.doi.org/10.1070/pu1996v039n08abeh001549.
Pełny tekst źródłaRozprawy doktorskie na temat "Localization density"
Lee, Chee Sing. "Simultaneous localization and mapping using single cluster probability hypothesis density filters". Doctoral thesis, Universitat de Girona, 2015. http://hdl.handle.net/10803/323637.
Pełny tekst źródłaEn aquesta tesis es desenvolupa aquest algoritme a partir d’un filtre PHD amb un únic grup (SC-PHD), una tècnica d’estimació multi-objecte basat en processos d’agrupació. Aquest algoritme té unes capacitats que normalment no es veuen en els algoritmes de SLAM basats en característiques, ja que és capaç de tractar falses característiques, així com característiques no detectades pels sensors del vehicle, a més de navegar en un entorn amb la presència de característiques estàtiques i característiques en moviment de forma simultània. Es presenten els resultats experimentals de l’algoritme SC-PHD en entorns reals i simulats utilitzant un vehicle autònom submarí. Els resultats són comparats amb l’algoritme de SLAM Rao-Blackwellized PHD (RB-PHD), demostrant que es requereixen menys aproximacions en la seva derivació i en conseqüència s’obté un rendiment superior.
Heinicke, Christiane. "Lithospheric-Scale Stresses and Shear Localization Induced by Density-Driven Instabilities". Thesis, Uppsala universitet, Geofysik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-183725.
Pełny tekst źródłaTorab, Leili. "The forward problem of EEG source localization using Current Density Imaging". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0020/MQ53445.pdf.
Pełny tekst źródłaLópez, Villafuerte Freddy [Verfasser]. "Localization of wireless sensor nodes based on local network density / Freddy López Villafuerte". Berlin : Freie Universität Berlin, 2010. http://d-nb.info/1024104060/34.
Pełny tekst źródłaDe, Santis Lorenzo. "Theory of electron Localization Function and its Applications: Surfaces, Impurities and Enzymatic Catalysis". Doctoral thesis, SISSA, 1999. http://hdl.handle.net/20.500.11767/4428.
Pełny tekst źródłaMazzarello, Riccardo. "Localization and density of states of disordered low-dimensional systems in a magnetic field". [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=971652023.
Pełny tekst źródłaDihidar, Souvik. "Applications of Low Density Parity Check Codes for Wiretap Channels and Congestion Localization in Networks". Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/13969.
Pełny tekst źródłaElesev, Aleksandr. "Robot Localization Using Inertial and RF Sensors". Miami University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=miami1218571607.
Pełny tekst źródłaMaffei, Renan de Queiroz. "Translating sensor measurements into texts for localization and mapping with mobile robots". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/158403.
Pełny tekst źródłaSimultaneous Localization and Mapping (SLAM), fundamental for building robots with true autonomy, is one of the most difficult problems in Robotics and consists of estimating the position of a robot that is moving in an unknown environment while incrementally building the map of such environment. Arguably the most crucial requirement to obtain proper localization and mapping is precise place recognition, that is, determining if the robot is at the same place in different occasions just by looking at the observations taken by the robot. Most approaches in literature are good when using highly expressive sensors such as cameras or when the robot is situated in low ambiguous environments. However this is not the case, for instance, using robots equipped only with range-finder sensors in highly ambiguous indoor structured environments. A good SLAM strategy must be able to handle these scenarios, deal with noise and observation errors, and, especially, model the environment and estimate the robot state in an efficient way. Our proposal in this work is to translate sequences of raw laser measurements into an efficient and compact text representation and deal with the place recognition problem using linguistic processing techniques. First, we translate raw sensor measurements into simple observation values computed through a novel observation model based on kernel-density estimation called Free-Space Density (FSD). These values are quantized into significant classes allowing the division of the environment into contiguous regions of homogeneous spatial density, such as corridors and corners. Regions are represented in a compact form by simple words composed of three syllables – the value of spatial density, the size and the variation of orientation of that region. At the end, the chains of words associated to all observations made by the robot compose a text, in which we search for matches of n-grams (i.e. sequences of words), which is a popular technique from shallow linguistic processing. The technique is also successfully applied in some scenarios of long-term operation, where we must deal with semi-static objects (i.e. that can move occasionally, such as doors and furniture). All approaches were evaluated in simulated and real scenarios obtaining good results.
MERICO, DAVIDE. "Tracking with high-density, large-scale wireless sensor networks". Doctoral thesis, Università degli Studi di Milano-Bicocca, 2010. http://hdl.handle.net/10281/7785.
Pełny tekst źródłaKsiążki na temat "Localization density"
Torab, Leili. The forward problem of EEG source localization using current density imaging. Ottawa: National Library of Canada, 2000.
Znajdź pełny tekst źródłaSchomer, Andrew, Margitta Seeck, Andres M. Kanner i Donald L. Schomer. Anterotemporal, Basal Temporal, Nasopharyngeal, and Sphenoidal Electrodes and High-Density Arrays. Redaktorzy Donald L. Schomer i Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0006.
Pełny tekst źródłaMichel, Christoph M., i Bin He. EEG Mapping and Source Imaging. Redaktorzy Donald L. Schomer i Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0045.
Pełny tekst źródłaHermans, Hubert J. M. The Dynamics of Society-in-the-Self. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190687793.003.0002.
Pełny tekst źródłaCzęści książek na temat "Localization density"
March, N. H. "Localization via Density Functionals". W Topics in Current Chemistry, 201–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48972-x_11.
Pełny tekst źródłaWegner, Franz. "Density Correlations Near the Mobility Edge". W Localization and Metal-Insulator Transitions, 337–46. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2517-8_27.
Pełny tekst źródłaContreras-García, Julia, Miriam Marqués, Bernard Silvi i José M. Recio. "Bonding Changes Along Solid-Solid Phase Transitions Using the Electron Localization Function Approach". W Modern Charge-Density Analysis, 625–58. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-3836-4_18.
Pełny tekst źródłaFang, Sheng En, Ricardo Perera i Maria Consuelo Huerta. "Damage Localization Based on Power Spectral Density Analysis". W Damage Assessment of Structures VII, 589–94. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-444-8.589.
Pełny tekst źródłaBorghesani, A. F., i M. Santini. "Excess Electron Localization in High-Density Neon Gas". W Linking the Gaseous and Condensed Phases of Matter, 281–301. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2540-0_18.
Pełny tekst źródłaLuo, Ye, Junsong Yuan, Ping Xue i Qi Tian. "Saliency Density Maximization for Object Detection and Localization". W Computer Vision – ACCV 2010, 396–408. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19318-7_31.
Pełny tekst źródłaDunstan, Rhys A., Iain D. Hay i Trevor Lithgow. "Defining Membrane Protein Localization by Isopycnic Density Gradients". W Methods in Molecular Biology, 81–86. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7033-9_6.
Pełny tekst źródłaDunstan, Rhys A., Iain D. Hay i Trevor Lithgow. "Defining Membrane Protein Localization by Isopycnic Density Gradients". W Methods in Molecular Biology, 91–98. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3445-5_6.
Pełny tekst źródłaChen, J., T. C. Chung, F. Moraes i A. J. Heeger. "First-Order Phase Transition to the Metallic State in Doped Polyacetylene: Solitons at High Density". W Localization and Metal-Insulator Transitions, 367–78. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2517-8_30.
Pełny tekst źródłaDattola, Serena, Fabio La Foresta, Lilla Bonanno, Simona De Salvo, Nadia Mammone, Silvia Marino i Francesco Carlo Morabito. "Effect of Sensor Density on eLORETA Source Localization Accuracy". W Neural Approaches to Dynamics of Signal Exchanges, 403–14. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8950-4_36.
Pełny tekst źródłaStreszczenia konferencji na temat "Localization density"
Kusy, Branislav, Akos Ledeczi, Miklos Maroti i Lambert Meertens. "Node density independent localization". W the fifth international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1127777.1127844.
Pełny tekst źródłaKusy, B., A. Ledeczi, M. Maroti i L. Meertens. "Node-density independent localization". W The Fifth International Conference on Information Processing in Sensor Networks. IEEE, 2006. http://dx.doi.org/10.1109/ipsn.2006.243912.
Pełny tekst źródłaKaroliny, Julian, Bernhard Etzlinger i Andreas Springer. "Mixture Density Networks for WSN Localization". W 2020 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2020. http://dx.doi.org/10.1109/iccworkshops49005.2020.9145035.
Pełny tekst źródłaZaarour, Nour, Nadir Hakem i NahiKandil. "Anchor Density Minimization for Localization in Wireless Sensor Network (WSN)". W 7th International Conference on Computer Science and Information Technology (CSTY 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.112201.
Pełny tekst źródłaLu, Ya, Ji Zhao i Jiayi Ma. "Object localization by density-based spatial clustering". W 2016 Visual Communications and Image Processing (VCIP). IEEE, 2016. http://dx.doi.org/10.1109/vcip.2016.7805515.
Pełny tekst źródłaBahi, Jacques M., Abdallah Makhoul i Ahmed Mostefaoui. "Localization and Coverage for High Density Sensor Networks". W Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07). IEEE, 2007. http://dx.doi.org/10.1109/percomw.2007.61.
Pełny tekst źródłaMaffei, Renan, Vitor A. M. Jorge, Vitor F. Rey, Mariana Kolberg i Edson Prestes. "Fast Monte Carlo Localization using spatial density information". W 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2015. http://dx.doi.org/10.1109/icra.2015.7140091.
Pełny tekst źródłaRibacki, Arthur, Vitor A. M. Jorge, Mathias Mantelli, Renan Maffei i Edson Prestes. "Vision-Based Global Localization Using Ceiling Space Density". W 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. http://dx.doi.org/10.1109/icra.2018.8460515.
Pełny tekst źródłaDogan, Refika Sultan, i Bulent Yilmaz. "Polyp Localization in Colonoscopy Images Using Vessel Density". W 2018 Medical Technologies National Congress (TIPTEKNO). IEEE, 2018. http://dx.doi.org/10.1109/tiptekno.2018.8597166.
Pełny tekst źródłaKemper, Jurgen, i Daniel Hauschildt. "Passive infrared localization with a Probability Hypothesis Density filter". W 2010 7th Workshop on Positioning, Navigation and Communication (WPNC). IEEE, 2010. http://dx.doi.org/10.1109/wpnc.2010.5653529.
Pełny tekst źródłaRaporty organizacyjne na temat "Localization density"
Gillespie, Douglas. 6th International workshop on the Detection, Classification, Localization and Density Estimation of Marine Mammals. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2013. http://dx.doi.org/10.21236/ada602542.
Pełny tekst źródłaMellinger, David K. Fifth International Workshop on Detection, Classification, Localization and Density Estimation of Marine Mammals using Passive Acoustics. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2012. http://dx.doi.org/10.21236/ada573558.
Pełny tekst źródłaMellinger, David K. Fifth International Workshop on Detection, Classification, Localization and Density Estimation of Marine Mammals using Passive Acoustics. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2013. http://dx.doi.org/10.21236/ada598544.
Pełny tekst źródłaChristie, Benjamin, Osama Ennasr i Garry Glaspell. ROS integrated object detection for SLAM in unknown, low-visibility environments. Engineer Research and Development Center (U.S.), listopad 2021. http://dx.doi.org/10.21079/11681/42385.
Pełny tekst źródłaRahmani, Mehran, Xintong Ji i Sovann Reach Kiet. Damage Detection and Damage Localization in Bridges with Low-Density Instrumentations Using the Wave-Method: Application to a Shake-Table Tested Bridge. Mineta Transportation Institute, wrzesień 2022. http://dx.doi.org/10.31979/mti.2022.2033.
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