Relevant bibliographies by topics / Localization analysis

Academic literature on the topic 'Localization analysis'

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Published: 10 March 2023

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Journal articles on the topic "Localization analysis"

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Suwannawach, Piyapan, and Sorawat Chivapreecha. "Reduce RSSI Variance for Indoor Localization System Using Frequency Analysis." International Journal of Future Computer and Communication 8, no. 2 (June 2019): 34–38. http://dx.doi.org/10.18178/ijfcc.2019.8.2.536.

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Lei, Lili, and Jeffrey S. Whitaker. "Model Space Localization Is Not Always Better Than Observation Space Localization for Assimilation of Satellite Radiances." Monthly Weather Review 143, no. 10 (October 1, 2015): 3948–55. http://dx.doi.org/10.1175/mwr-d-14-00413.1.

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Abstract Covariance localization is an essential component of ensemble-based data assimilation systems for large geophysical applications with limited ensemble sizes. For integral observations like the satellite radiances, where the concepts of location or vertical distance are not well defined, vertical localization in observation space is not as straightforward as in model space. The detailed differences between model space and observation space localizations are examined using a real radiance observation. Counterintuitive analysis increments can be obtained with model space localization; the magnitude of the increment can increase and the increment can change sign when the localization scale decreases. This occurs when there are negative background-error covariances and a predominately positive forward operator. Too narrow model space localization can neglect the negative background-error covariances and result in the counterintuitive analysis increments. An idealized 1D model with integral observations and known true error covariance is then used to compare errors resulting from model space and observation space localizations. Although previous studies have suggested that observation space localization is inferior to model space localization for satellite radiances, the results from the 1D model reveal that observation space localization can have advantages over model space localization when there are negative background-error covariances. Differences between model space and observation space localizations disappear as ensemble size, observation error variance, and localization scale increase. Thus, large ensemble sizes and vertical localization length scales may be needed to more effectively assimilate radiance observations.
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Cordero, Elena, and Karlheinz Gröchenig. "Time–Frequency analysis of localization operators." Journal of Functional Analysis 205, no. 1 (December 2003): 107–31. http://dx.doi.org/10.1016/s0022-1236(03)00166-6.

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von Brecht, James H. "Localization and vector spherical harmonics." Journal of Differential Equations 260, no. 2 (January 2016): 1622–55. http://dx.doi.org/10.1016/j.jde.2015.09.041.

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Bindel, David, and Amanda Hood. "Localization Theorems for Nonlinear Eigenvalue Problems." SIAM Journal on Matrix Analysis and Applications 34, no. 4 (January 2013): 1728–49. http://dx.doi.org/10.1137/130913651.

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Pushnitski, Alexander, and Dmitri Yafaev. "Localization principle for compact Hankel operators." Journal of Functional Analysis 270, no. 9 (May 2016): 3591–621. http://dx.doi.org/10.1016/j.jfa.2015.10.018.

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Elgart, Alexander, and Abel Klein. "An eigensystem approach to Anderson localization." Journal of Functional Analysis 271, no. 12 (December 2016): 3465–512. http://dx.doi.org/10.1016/j.jfa.2016.09.008.

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Faris, William G. "A localization principle for multiplicative perturbations." Journal of Functional Analysis 67, no. 1 (June 1986): 105–14. http://dx.doi.org/10.1016/0022-1236(86)90045-5.

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Taliaferro, J. Matthew, Eric T. Wang, and Christopher B. Burge. "Genomic analysis of RNA localization." RNA Biology 11, no. 8 (August 3, 2014): 1040–50. http://dx.doi.org/10.4161/rna.32146.

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Wallace, John S., Donald L. Fisher, and John Collura. "Sound Localization: Information Theory Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 18 (October 1996): 905–9. http://dx.doi.org/10.1177/154193129604001808.

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Three experiments were performed which examined the applicability of the Hick-Hyman law to the design of an auditory interface for a vehicle collision avoidance warning system. All trials used a single broadband noise signal emanating from one of a subset of six loudspeakers equally spaced around the subject in the azimuthal plane. Both the size of the sub-set and the balance of relative probabilities from speaker to speaker were altered to evaluate the relationship between information content and the dependent variable, choice reaction time. Choice reaction time was found to be related to the information content of the sound stimulus in all cases. It was also found to be related to the presence of pairs of speakers which were symmetrically opposed to one another in front of and behind the subject.
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Dissertations / Theses on the topic "Localization analysis"

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Baah, George Kofi. "Statistical causal analysis for fault localization." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45762.

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The ubiquitous nature of software demands that software is released without faults. However, software developers inadvertently introduce faults into software during development. To remove the faults in software, one of the tasks developers perform is debugging. However, debugging is a difficult, tedious, and time-consuming process. Several semi-automated techniques have been developed to reduce the burden on the developer during debugging. These techniques consist of experimental, statistical, and program-structure based techniques. Most of the debugging techniques address the part of the debugging process that relates to finding the location of the fault, which is referred to as fault localization. The current fault-localization techniques have several limitations. Some of the limitations of the techniques include (1) problems with program semantics, (2) the requirement for automated oracles, which in practice are difficult if not impossible to develop, and (3) the lack of theoretical basis for addressing the fault-localization problem. The thesis of this dissertation is that statistical causal analysis combined with program analysis is a feasible and effective approach to finding the causes of software failures. The overall goal of this research is to significantly extend the state of the art in fault localization. To extend the state-of-the-art, a novel probabilistic model that combines program-analysis information with statistical information in a principled manner is developed. The model known as the probabilistic program dependence graph (PPDG) is applied to the fault-localization problem. The insights gained from applying the PPDG to fault localization fuels the development of a novel theoretical framework for fault localization based on established causal inference methodology. The development of the framework enables current statistical fault-localization metrics to be analyzed from a causal perspective. The analysis of the metrics show that the metrics are related to each other thereby allowing the unification of the metrics. Also, the analysis of metrics from a causal perspective reveal that the current statistical techniques do not find the causes of program failures instead the techniques find the program elements most associated with failures. However, the fault-localization problem is a causal problem and statistical association does not imply causation. Several empirical studies are conducted on several software subjects and the results (1) confirm our analytical results, (2) demonstrate the efficacy of our causal technique for fault localization. The results demonstrate the research in this dissertation significantly improves on the state-of-the-art in fault localization.
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Shah, Zubin. "SIMULATION AND ANALYSIS OF RFID LOCALIZATION ALGORITHMS." Wright State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=wright1164732791.

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Schubert, Roman. "Semiclassical localization in phase space." Ulm : Universität Ulm, Fakultät für Naturwissenschaften, 2001. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10028611.

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Liu, Guanxiong. "Modeling and Performance Analysis of Hybrid Localization Using Inertial Sensor, RFID and Wi-Fi Signal." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/514.

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The development in wireless technology, mobile smart devices and Internet of Things has gave birth to a booming era or the wireless indoor geolocation. This technology have been increasingly used within our daily life and help people to build up the tracking system which could be used by fulfillment centers and grocery stores. To achieve higher localization accuracy with wireless geolocation, we need a higher density of deployment which involves high deployment and maintenance cost. To balance the accuracy and the cost, people have begun using wireless localization employing inertial navigation system (INS) which provide speed and direction of movement. When we combine Radio Frequency (RF) localization with INS, we have a hybrid INS/RF localization system which can achieve high localization accuracy with low cost. In this thesis, we use accelerometers and magnetometers in an Android smart phone to build a hybrid INS/RF system and use two different technologies for RF localization: Radio Frequency Identification Device (RFID) and Wi-Fi. Using this system, we conducted measurements of the hybrid localization system and evaluate its performance. The specific contributions of the thesis are: (1)Empirical performance evaluation of the INS/RFID localization system. It relates the localization error to the number and position of RFID tags. (2)Model the effect of metallic objects on accuracy of magnetometer. The model shows the relation between direction error and distance to metallic component. (3)Model shadow fading in close proximity of RF transmitter. It builds a distance dependent shadow fading model. (4)Model based performance evaluation of hybrid localization. The test bench uses our models to simulate the hybrid localization data.
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Ali, Andreas Mantik. "Distributed acoustic localization and tracking design and analysis." Diss., Restricted to subscribing institutions, 2010. http://proquest.umi.com/pqdweb?did=2023768071&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Hu, Peifeng. "Automated fault localization a statistical predicate analysis approach /." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B38838035.

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Hu, Peifeng, and 胡佩鋒. "Automated fault localization: a statistical predicate analysis approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B38838035.

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Zahran, Saeed. "Source localization and connectivity analysis of uterine activity." Thesis, Compiègne, 2018. http://www.theses.fr/2018COMP2469.

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La technique d'EHGI permet une reconstruction non invasive du potentiel électrique à la surface de l’utérus à partir du potentiel électrique mesuré à la surface du corps et des données anatomiques du torse. L’EHGI fournit des informations très précieuses sur l'état de l’utérus car il est capable de fournir une description spatiale raffinée de la voie et de l’amplitude des ondes électriques à la surface de l'utérus. Cela peut aider beaucoup dans différentes interventions cliniques. Les algorithmes scientifiques derrière tout outil EHGI sont capables de prétraiter les données anatomiques du patient afin de fournir un maillage informatique, de filtrer les mesures bruitées du potentiel électrique et de résoudre un problème inverse. Le problème inverse en électrohystérographie utérine (imagerie électrohystérographique (EHGI)) est une technique de diagnostic nouvelle et puissante. Cette technologie non invasive intéresse de plus en plus les industries médicales. Le succès de cette technologie serait considéré comme une percée dans le diagnostic de l'utérus. Cependant, dans de nombreux cas, la qualité du potentiel électrique reconstruit n’est pas suffisamment précise. La difficulté vient du fait que le problème inverse en électrohystérographie utérine est bien connu comme un problème mathématiquement mal posé. Différentes méthodes basées sur la régularisation de Thikhnov ont été utilisées afin de régulariser le problème. Nous avons mené notre analyse en utilisant un modèle d’utérus réaliste et avons cherché à identifier l’étendue spatiale des sources
The technique of EHGI allows a noninvasive reconstruction of the electrical potential on the uterus surface based on electrical potential measured on the body surface and anatomical data of the torso. EHGI provides very precious information about the uterus condition since it is able to provide refined spatial description of the electrical wave pathway and magnitude on the uterus surface. This may help a lot in different clinical interventions. The scientific algorithms behind any EHGI tool are able to preprocess the anatomical data of the patient in order to provide a computational mesh, filter noisy measurements of the electrical potential and solve an inverse problem. The inverse problem in uterus electrohysterography (electrohysterography imaging (EHGI)) is a new and a powerful diagnosis technique. This non-invasive technology interests more and more medical industries. The success of this technology would be considered as a breakthrough in the uterus diagnosis. However, in many cases the quality of reconstructed electrical potential is not accurate enough. The difficulty comes from the fact that the inverse problem in uterus electrohysterography is well known as a mathematically ill-posed problem. Different methods based on Thikhnov regularization have been used in order to regularize the problem. We have conducted our analysis by using a realistic uterus model and have aimed at identifying the spatial extent of the sources
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Bäck, Viktor. "Localization of Multiscale Screened Poisson Equation." Thesis, Uppsala universitet, Algebra och geometri, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-180928.

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Liu, Changlin. "Root Cause Localization for Unreproducible Builds." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1595524817828183.

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Books on the topic "Localization analysis"

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Jatoi, Munsif Ali, and Nidal Kamel. Brain Source Localization Using EEG Signal Analysis. Boca Raton : Taylor & Francis, 2018.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315156415.

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J, Allan Victoria, ed. Protein localization by fluorescence microscopy: A practical approach. Oxford: Oxford University Press, 2000.

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1925-, Pertschuk Louis P., and Lee Sin Hang 1932-, eds. Localization of putative steroid receptors. Boca Raton. Fla: CRC Press, 1985.

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Rucka, Magdalena. Application of wavelet analysis in damage detection and localization. Gdańsk: Wydawn. Politechniki Gdańskiej, 2007.

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Localization and perturbation of zeros of entire functions. Boca Raton: Chapman & Hall/CRC, 2009.

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Murmanis, L. Cytochemical localization of cellulases in decayed and nondecayed wood. [Madison, Wis.?: Forest Products Laboratory], 1987.

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Vorozht͡sov, E. V. Methods for the localization of singularities in numerical solutions of gas dynamics problems. New York: Springer-Verlag, 1990.

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M, Rakowicz-Szulczynska Ewa, ed. Nuclear localization of growth factors and of monoclonal antibodies. Boca Raton: CRC Press, 1994.

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Madej, Łukasz. Development of the modelling strategy for the strain localization simulation based on the digital material representation. Kraków: AGH University of Science and Technology Press, 2010.

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Miguel Torre do Vale Arriaga e Cunha. Stability Analysis of Metals Capturing Brittle and Ductile Fracture through a Phase Field Method and Shear Band Localization. [New York, N.Y.?]: [publisher not identified], 2016.

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Book chapters on the topic "Localization analysis"

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Zhang, Zhengyou, and Olivier Faugeras. "Object Recognition and Localization." In 3D Dynamic Scene Analysis, 159–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-58148-9_10.

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Garro, Valeria, Maurizio Galassi, and Andrea Fusiello. "Wide Area Camera Localization." In Image Analysis and Processing – ICIAP 2013, 320–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41181-6_33.

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So, H. C. "Source Localization: Algorithms and Analysis." In Handbook of Position Location, 25–66. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118104750.ch2.

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Aboul Naga, Ramy, Rimon Elias, and Amal El Nahas. "Indoor Localization Using Cluster Analysis." In Artificial Intelligence and Soft Computing, 3–13. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20915-5_1.

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Lin, Liang, Dongyu Zhang, Ping Luo, and Wangmeng Zuo. "Face Localization and Enhancement." In Human Centric Visual Analysis with Deep Learning, 29–45. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2387-4_3.

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Kabara, J. J. "Determination and Microscopic Localization of Cholesterol." In Methods of Biochemical Analysis, 263–318. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470110270.ch9.

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Zarka, Joseph, Joel Frelat, and Sahbi Braham. "Simplified Analysis of Elastoplastic Structures." In Anisotropy and Localization of Plastic Deformation, 684–87. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3644-0_160.

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Campadelli, Paola, Raffaella Lanzarotti, Giuseppe Lipori, and Eleonora Salvi. "Face and Facial Feature Localization." In Image Analysis and Processing – ICIAP 2005, 1002–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11553595_123.

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Boegner, F., and P. Marx. "Bilateral Thalamic Infarction: A Contribution to Coma Analysis." In Brain-Stem Localization and Function, 45–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78172-8_5.

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Alomari, Raja S., Subarna Ghosh, Jaehan Koh, and Vipin Chaudhary. "Vertebral Column Localization, Labeling, and Segmentation." In Spinal Imaging and Image Analysis, 193–229. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12508-4_7.

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Conference papers on the topic "Localization analysis"

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BLANCHARD, PH, M. PASQUINI, and M. SERVA. "CLASSICAL LIMIT: LOCALIZATION INDUCED BY NOISE." In Historical Analysis and Open Questions. WORLD SCIENTIFIC, 2000. http://dx.doi.org/10.1142/9789812793560_0004.

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Park, Chang-Woo, and Jung-Hoon Hwang. "Mobile Robot Localization for Logistics Environment." In Adaptive Optics: Analysis, Methods & Systems. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.jt5a.23.

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Frankl, Phyllis. "Session details: Fault localization." In ISSTA '09: International Symposium on Software Testing and Analysis. New York, NY, USA: ACM, 2009. http://dx.doi.org/10.1145/3261151.

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Ernst, Michael. "Session details: Fault localization." In ISSTA '08: International Symposium on Software Testing and Analysis. New York, NY, USA: ACM, 2008. http://dx.doi.org/10.1145/3260630.

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Cernigliaro, Alice, Stefano Valloreia, Lorenzo Galleani, and Patrizia Tavella. "GNSS space clocks: Performance analysis." In 2013 International Conference on Localization and GNSS (ICL-GNSS). IEEE, 2013. http://dx.doi.org/10.1109/icl-gnss.2013.6577251.

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Sha, Yoshitomo, Masataka Nagura, and Shingo Takada. "Fault Localization in Server-Side Applications Using Spectrum-Based Fault Localization." In 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE, 2022. http://dx.doi.org/10.1109/saner53432.2022.00131.

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Mori Gonzalez, G., I. Petrunin, R. Zbikowski, K. Voutsis, and R. Verdeguer Moreno. "Vulnerability Analysis of GPS Receiver Software." In 2019 International Conference on Localization and GNSS (ICL-GNSS). IEEE, 2019. http://dx.doi.org/10.1109/icl-gnss.2019.8752862.

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Flandrin, P. "On time-frequency localization." In IEE Seminar on Time-Scale and Time-Frequency Analysis and Applications. IEE, 2000. http://dx.doi.org/10.1049/ic:20000550.

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Xu Huiyan and Wang Jingfang. "Real-time iris localization method." In 2011 International Conference on Image Analysis and Signal Processing (IASP). IEEE, 2011. http://dx.doi.org/10.1109/iasp.2011.6109058.

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Popov, Vladimir. "Fingerprints selection for topological localization." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2016). Author(s), 2017. http://dx.doi.org/10.1063/1.4992728.

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Reports on the topic "Localization analysis"

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McCarty, Peter E., Marton I. Garay, Mary R. Parse, and Russell E. Henrichs. ADS MNT and FET: Array Element Localization Analysis and Results. Fort Belvoir, VA: Defense Technical Information Center, March 2000. http://dx.doi.org/10.21236/ada389866.

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Englot, Brendan J. Stability and Robustness Analysis Tools for Marine Robot Localization and Mapping Applications. Fort Belvoir, VA: Defense Technical Information Center, June 2009. http://dx.doi.org/10.21236/ada507889.

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Wang, Jian-Li, Bao-Zhong Ding, Feng-Fei Xia, and Er-Liang Li. Preoperative computed tomography-guided localization for multiple lung nodules: a meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0028.

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Du, Jiang, Yu-Fei Fu, and Ya-Nan Lv. Preoperative localization for lung nodules: a meta-analysis of bronchoscopic versus computed tomography guidance. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, June 2022. http://dx.doi.org/10.37766/inplasy2022.6.0068.

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Solomon, Latasha, Yirong Pu, and Allyn Hubbard. Acoustic Transient Localization: A Comparative Analysis of the Conventional Time Difference of Arrival Versus Biomimetics. Fort Belvoir, VA: Defense Technical Information Center, November 2009. http://dx.doi.org/10.21236/ada512484.

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Armero, Francisco. Analysis and Numerical Simulation of Strain Localization in Inelastic Solids Under Fully Coupled Thermomechanical and Poroplastic Conditions. Fort Belvoir, VA: Defense Technical Information Center, August 2000. http://dx.doi.org/10.21236/ada380940.

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LeBrun, Thomas John. Analysis of Compact-Forced Simple Shear and Compact-Forced Double Shear Test Specimens for Shear Localization in Materials. Office of Scientific and Technical Information (OSTI), May 2017. http://dx.doi.org/10.2172/1356162.

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Wang, Jian-Li, Feng-Fei Xia, and Yun Lu. Comparison between coil and hook-wire localization before video-assisted thoracoscopic surgery for lung nodules: a meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2022. http://dx.doi.org/10.37766/inplasy2022.3.0128.

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Chang, Ke-Vin. Deep Learning Algorithm for Automatic Localization and Segmentation of the Median Nerve: a Protocol for Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, May 2022. http://dx.doi.org/10.37766/inplasy2022.5.0074.

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Review question / Objective: To explore/summarize the performance of deep learning in automatic localization and segmentation of the median nerve at the carpal tunnel level. Condition being studied: Participants with and without carpal tunnel syndrome. Information sources: The following electronic databases will be searched, encompassing PubMed, Medline, Embase and Web of Science. We target the studies investigating in the utility of deep neural network on the evaluation of the median nerve in the carpal tunnel.
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Lenz, Janet, Stephen Leierer, Robert Reardon, and James Sampson. An Analysis of the Localization Feature of Two Computer-Assisted Career Guidance Systems - DISCOVER and SIGI PLUS: Technical Report No. 14. Florida State University Libraries, June 1992. http://dx.doi.org/10.17125/fsu.1525888624.

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