Literatura académica sobre el tema "Localization density"
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Artículos de revistas sobre el tema "Localization density"
Gadre, Shridhar R., Sudhir A. Kulkarni y Rajeev K. Pathak. "Density‐based electron localization function via nonlocal density approximation". Journal of Chemical Physics 98, n.º 4 (15 de febrero de 1993): 3574–76. http://dx.doi.org/10.1063/1.464082.
Texto completoMovaghar, B. "Localization and the density of states". Philosophical Magazine B 65, n.º 5 (mayo de 1992): 1097–108. http://dx.doi.org/10.1080/13642819208217923.
Texto completoBalan, Radu, Peter G. Casazza, Christopher Heil y Zeph Landau. "Density, overcompleteness, and localization of frames". Electronic Research Announcements of the American Mathematical Society 12, n.º 10 (7 de julio de 2006): 71–86. http://dx.doi.org/10.1090/s1079-6762-06-00163-6.
Texto completoHutník, Ondrej, Egor A. Maximenko y Anna Mišková. "Toeplitz Localization Operators: Spectral Functions Density". Complex Analysis and Operator Theory 10, n.º 8 (20 de mayo de 2016): 1757–74. http://dx.doi.org/10.1007/s11785-016-0564-1.
Texto completoPilmé, Julien. "Electron localization function from density components". Journal of Computational Chemistry 38, n.º 4 (17 de noviembre de 2016): 204–10. http://dx.doi.org/10.1002/jcc.24672.
Texto completoSchroer, Bert. "Area density of localization entropy: I. The case of wedge localization". Classical and Quantum Gravity 23, n.º 17 (7 de agosto de 2006): 5227–48. http://dx.doi.org/10.1088/0264-9381/23/17/008.
Texto completoBouhdid, Badia, Wafa Akkari y Sofien Gannouni. "Low Cost Recursive Localization scheme for High Density Wireless Sensor Networks". International Journal on Semantic Web and Information Systems 13, n.º 3 (julio de 2017): 68–88. http://dx.doi.org/10.4018/ijswis.2017070104.
Texto completoSuslov, Igor' M. "Density of states near the localization threshold". Uspekhi Fizicheskih Nauk 166, n.º 8 (1996): 907. http://dx.doi.org/10.3367/ufnr.0166.199608x.0907.
Texto completoMarsh, Richard J., Karin Pfisterer, Pauline Bennett, Liisa M. Hirvonen, Mathias Gautel, Gareth E. Jones y Susan Cox. "Artifact-free high-density localization microscopy analysis". Nature Methods 15, n.º 9 (30 de julio de 2018): 689–92. http://dx.doi.org/10.1038/s41592-018-0072-5.
Texto completoSuslov, Igor' M. "Density of states near the localization threshold". Physics-Uspekhi 39, n.º 8 (31 de agosto de 1996): 848–49. http://dx.doi.org/10.1070/pu1996v039n08abeh001549.
Texto completoTesis sobre el tema "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.
Texto completoEn 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.
Texto completoTorab, 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.
Texto completoLópez, 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.
Texto completoDe, 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.
Texto completoMazzarello, 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.
Texto completoDihidar, 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.
Texto completoElesev, Aleksandr. "Robot Localization Using Inertial and RF Sensors". Miami University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=miami1218571607.
Texto completoMaffei, 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.
Texto completoSimultaneous 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.
Texto completoLibros sobre el tema "Localization density"
Torab, Leili. The forward problem of EEG source localization using current density imaging. Ottawa: National Library of Canada, 2000.
Buscar texto completoSchomer, Andrew, Margitta Seeck, Andres M. Kanner y Donald L. Schomer. Anterotemporal, Basal Temporal, Nasopharyngeal, and Sphenoidal Electrodes and High-Density Arrays. Editado por Donald L. Schomer y Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0006.
Texto completoMichel, Christoph M. y Bin He. EEG Mapping and Source Imaging. Editado por Donald L. Schomer y Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0045.
Texto completoHermans, Hubert J. M. The Dynamics of Society-in-the-Self. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190687793.003.0002.
Texto completoCapítulos de libros sobre el tema "Localization density"
March, N. H. "Localization via Density Functionals". En Topics in Current Chemistry, 201–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48972-x_11.
Texto completoWegner, Franz. "Density Correlations Near the Mobility Edge". En Localization and Metal-Insulator Transitions, 337–46. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2517-8_27.
Texto completoContreras-García, Julia, Miriam Marqués, Bernard Silvi y José M. Recio. "Bonding Changes Along Solid-Solid Phase Transitions Using the Electron Localization Function Approach". En Modern Charge-Density Analysis, 625–58. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-3836-4_18.
Texto completoFang, Sheng En, Ricardo Perera y Maria Consuelo Huerta. "Damage Localization Based on Power Spectral Density Analysis". En Damage Assessment of Structures VII, 589–94. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-444-8.589.
Texto completoBorghesani, A. F. y M. Santini. "Excess Electron Localization in High-Density Neon Gas". En 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.
Texto completoLuo, Ye, Junsong Yuan, Ping Xue y Qi Tian. "Saliency Density Maximization for Object Detection and Localization". En Computer Vision – ACCV 2010, 396–408. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19318-7_31.
Texto completoDunstan, Rhys A., Iain D. Hay y Trevor Lithgow. "Defining Membrane Protein Localization by Isopycnic Density Gradients". En 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.
Texto completoDunstan, Rhys A., Iain D. Hay y Trevor Lithgow. "Defining Membrane Protein Localization by Isopycnic Density Gradients". En Methods in Molecular Biology, 91–98. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3445-5_6.
Texto completoChen, J., T. C. Chung, F. Moraes y A. J. Heeger. "First-Order Phase Transition to the Metallic State in Doped Polyacetylene: Solitons at High Density". En Localization and Metal-Insulator Transitions, 367–78. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2517-8_30.
Texto completoDattola, Serena, Fabio La Foresta, Lilla Bonanno, Simona De Salvo, Nadia Mammone, Silvia Marino y Francesco Carlo Morabito. "Effect of Sensor Density on eLORETA Source Localization Accuracy". En 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.
Texto completoActas de conferencias sobre el tema "Localization density"
Kusy, Branislav, Akos Ledeczi, Miklos Maroti y Lambert Meertens. "Node density independent localization". En the fifth international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1127777.1127844.
Texto completoKusy, B., A. Ledeczi, M. Maroti y L. Meertens. "Node-density independent localization". En The Fifth International Conference on Information Processing in Sensor Networks. IEEE, 2006. http://dx.doi.org/10.1109/ipsn.2006.243912.
Texto completoKaroliny, Julian, Bernhard Etzlinger y Andreas Springer. "Mixture Density Networks for WSN Localization". En 2020 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2020. http://dx.doi.org/10.1109/iccworkshops49005.2020.9145035.
Texto completoZaarour, Nour, Nadir Hakem y NahiKandil. "Anchor Density Minimization for Localization in Wireless Sensor Network (WSN)". En 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.
Texto completoLu, Ya, Ji Zhao y Jiayi Ma. "Object localization by density-based spatial clustering". En 2016 Visual Communications and Image Processing (VCIP). IEEE, 2016. http://dx.doi.org/10.1109/vcip.2016.7805515.
Texto completoBahi, Jacques M., Abdallah Makhoul y Ahmed Mostefaoui. "Localization and Coverage for High Density Sensor Networks". En Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07). IEEE, 2007. http://dx.doi.org/10.1109/percomw.2007.61.
Texto completoMaffei, Renan, Vitor A. M. Jorge, Vitor F. Rey, Mariana Kolberg y Edson Prestes. "Fast Monte Carlo Localization using spatial density information". En 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2015. http://dx.doi.org/10.1109/icra.2015.7140091.
Texto completoRibacki, Arthur, Vitor A. M. Jorge, Mathias Mantelli, Renan Maffei y Edson Prestes. "Vision-Based Global Localization Using Ceiling Space Density". En 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. http://dx.doi.org/10.1109/icra.2018.8460515.
Texto completoDogan, Refika Sultan y Bulent Yilmaz. "Polyp Localization in Colonoscopy Images Using Vessel Density". En 2018 Medical Technologies National Congress (TIPTEKNO). IEEE, 2018. http://dx.doi.org/10.1109/tiptekno.2018.8597166.
Texto completoKemper, Jurgen y Daniel Hauschildt. "Passive infrared localization with a Probability Hypothesis Density filter". En 2010 7th Workshop on Positioning, Navigation and Communication (WPNC). IEEE, 2010. http://dx.doi.org/10.1109/wpnc.2010.5653529.
Texto completoInformes sobre el tema "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, septiembre de 2013. http://dx.doi.org/10.21236/ada602542.
Texto completoMellinger, 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, septiembre de 2012. http://dx.doi.org/10.21236/ada573558.
Texto completoMellinger, 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, septiembre de 2013. http://dx.doi.org/10.21236/ada598544.
Texto completoChristie, Benjamin, Osama Ennasr y Garry Glaspell. ROS integrated object detection for SLAM in unknown, low-visibility environments. Engineer Research and Development Center (U.S.), noviembre de 2021. http://dx.doi.org/10.21079/11681/42385.
Texto completoRahmani, Mehran, Xintong Ji y 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, septiembre de 2022. http://dx.doi.org/10.31979/mti.2022.2033.
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