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Relevant bibliographies by topics / Prefiltering

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Academic literature on the topic 'Prefiltering'

Author: Grafiati

Published: 3 June 2025

Last updated: 19 July 2025

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Journal articles on the topic "Prefiltering"

1

Tian-Tsong Ng and Shih-Fu Chang. "Identifying and prefiltering images." IEEE Signal Processing Magazine 26, no. 2 (2009): 49–58. http://dx.doi.org/10.1109/msp.2008.931077.

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Itoh, Katsuko, Tetsuya Shimamura, and Jouji Suzuki. "Prefiltering for blind equalization." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 78, no. 9 (1995): 1–11. http://dx.doi.org/10.1002/ecjc.4430780901.

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Kumaresan, R., and Y. Feng. "FIR prefiltering improves Prony's method." IEEE Transactions on Signal Processing 39, no. 3 (1991): 736–41. http://dx.doi.org/10.1109/78.80860.

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Hong, X., P. A. Wilson, and C. J. Harris. "Neurofuzzy state identification using prefiltering." IEE Proceedings - Control Theory and Applications 146, no. 2 (1999): 234–40. http://dx.doi.org/10.1049/ip-cta:19990121.

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Greenhalgh, P. A., R. D. Abel, and P. A. Davuies. "Optical prefiltering in subcarrier systems." Electronics Letters 28, no. 19 (1992): 1850. http://dx.doi.org/10.1049/el:19921180.

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Lindner, R. "A Prefiltering Raster Scan Algorithm." Computer Graphics Forum 4, no. 2 (1985): 101–10. http://dx.doi.org/10.1111/j.1467-8659.1985.tb00199.x.

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Ghayekhloo, Samira, and Zeki Bayram. "Prefiltering Strategy to Improve Performance of Semantic Web Service Discovery." Scientific Programming 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/576463.

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Discovery of semantic Web services is a heavyweight task when the number of Web services or the complexity of ontologies increases. In this paper, we present a new logical discovery framework based on semantic description of the capability of Web services and user goals using F-logic. Our framework tackles the scalability problem and improves discovery performance by adding two prefiltering stages to the discovery engine. The first stage is based on ontology comparison of user request and Web service categories. In the second stage, yet more Web services are eliminated based upon a decomposition and analysis of concept and instance attributes used in Web service capabilities and the requested capabilities of the client, resulting in a much smaller pool of Web services that need to be matched against the client request. Our prefiltering approach is evaluated using a new Web service repository, called WSMO-FL test collection. The recall rate of the filtering process is 100% by design, since no relevant Web services are ever eliminated by the two prefiltering stages, and experimental results show that the precision rate is more than 53%.

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Ramachandra, Vikas, Keigo Hirakawa, Matthias Zwicker, and Truong Nguyen. "Spatioangular Prefiltering for Multiview 3D Displays." IEEE Transactions on Visualization and Computer Graphics 17, no. 5 (2011): 642–54. http://dx.doi.org/10.1109/tvcg.2010.86.

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Vrhel, M. J., and A. Aldroubi. "Projection based prefiltering for multiwavelet transforms." IEEE Transactions on Signal Processing 46, no. 11 (1998): 3088–92. http://dx.doi.org/10.1109/78.726821.

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Hildebrand, R., A. Lecchini, G. Solari, and M. Gevers. "Optimal prefiltering in iterative feedback tuning." IEEE Transactions on Automatic Control 50, no. 8 (2005): 1196–200. http://dx.doi.org/10.1109/tac.2005.852554.

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Dissertations / Theses on the topic "Prefiltering"

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Abel, R. D. "Optical prefiltering in subcarrier systems." Thesis, University of Kent, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262367.

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Kiessling, Mario [Verfasser]. "Statistical Analysis and Transmit Prefiltering for MIMO Wireless Systems in Correlated Fading Environments / Mario Kiessling." Aachen : Shaker, 2004. http://d-nb.info/1172613060/34.

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Nilsson, Linus. "Quality and real-time performance assessment of color-correction methods : A comparison between histogram-based prefiltering and global color transfer." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-33877.

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In the field of computer vision and more specifically multi-camera systems color correction is an important topic of discussion. The need for color-tone similarity among multiple images that are used to construct a single scene is self-evident. The strength and weaknesses of color- correction methods can be assessed by using metrics to measure structural and color-tone similarity and timing the methods. Color transfer has a better structural similarity than histogram-based prefiltering and a worse color-tone similarity. The color transfer method is faster than the histogram-based prefiltering. Color transfer is a better method if the focus is a structural similar image after correction, if better color-tone similarity at the cost of structural similarity is acceptable histogram-based prefiltering is a better choice. Color transfer is a faster method and is easier to run with a parallel computing approach then histogram-based prefiltering. Color transfer might therefore be a better pick for real-time applications. There is however more room to optimize an implementation of histogram-based prefiltering utilizing parallel computing.

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Auksutienė, Daiva. "Prony klasės metodų taikymo signalų įvertinimui tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2004. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2004~D_20040611_155300-33626.

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A possibility for parametric signal estimation by Prony class methods is investigated in this work. So-called exponential-sinusoidal models are considered. These models comprise damped exponentials, damped and undamped sinusoidals, and various their additive combinations. Two main methods – the classical Prony method and Prony method with prefiltering – are studied in this work. The formulas for estimation of parameters of undamped and damped sinusoidals by the classical Prony method are derived. The algorithm for calculation of the impulse response of the filter used in Prony method with prefiltering is given. Software for estimation of exponential-sinusoidal models by Prony class methods is developed (in the MATLAB environment). Numerical experiments are carried out using the software developed. The conclusions on possibilities of application of the classical Prony method and Prony method with prefiltering are stated on the basis of simulation results.

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Liu, Chi-Fang, and 劉其芳. "Fourth-Power Law Clock Recovery with Prefiltering." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/30895208288240026300.

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Lin, Han-En, and 林涵恩. "Image-based Prefiltering for Space Checking on post-OPC Layout." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/32414009562114355385.

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碩士<br>國立交通大學<br>資訊科學與工程研究所<br>98<br>In recent years, optical proximity correction (OPC) technology has been widely used in semiconductor industry. Some software has been applied to simulate the exposure results for OPC photomask while other software has been used to check the (simulated) etched circuit for process constraints such as minimum spacing/width. These constraints are defined to avoid electrical failures such as bridge and pinch. This thesis research proposes an efficient algorithm to check the spacing of the OPC simulation results. The algorithm first applies a pre-filter to rapidly check minimum the spacing using low-resolution image. Sub-images for areas which may cause bridges are then restored with high resolution, through interpolation, to facilitate more precise examination of the spacing. Some preliminary experimental results show that the proposed system can provide required analyses satisfactorily in terms of accuracy and speed.

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Huang, Chia-Hsin, and 黃嘉新. "Developing GML-native Web-based Geographic Information Systems Using XML Prefiltering Techniques." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/38078433485730790061.

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博士<br>國立臺灣科技大學<br>電子工程系<br>97<br>Most geographic information systems (GISs) use relational databases to manipulate information efficiently. They however suffer from interoperability issues because they need to expend significant effort mapping heterogeneous geographic information, which may have complicated structures, into relational data models, and vice versa. Geography Markup Language (GML) is regarded as a standard for expressing, storing, and exchanging geospatial data, and has been applied to help solve interoperability problems. Interestingly, no GIS has been built on native XML/GML technologies so far. There are two possible reasons for this: current XML processors are incapable of processing geospatial information, and they are inefficient in manipulating large XML documents. In this paper, we resolve these two difficulties and move forward to realizing GML-native Web-based geographic information systems. Specifically, we develop an XML/GML prefilter for enhancing query performance in the GML-native Web-based GISs as well as other generic XML processors. The prefilter is an efficient, small-scale, lightweight, minimal intrusive, and transparent technique for improving XML processing in large documents. The prefilter essentially uses a tiny search engine to locate interesting fragments in the source XML documents by approximately executing the user's queries. The interesting fragments and some necessary structural information are gathered into a candidate-set XML document that is returned to the XML applications for further processing. The prefilter can either reduce computational resources or lower query execution time. Depending on the nature of user queries, the enhanced query processors can reach ten-fold performance improvement, while an overhead of about 10~15% would incur for answering queries that return almost the entire documents.

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Hung-YuSu and 蘇泓諭. "Tree Search Detection Algorithms with Frequency-Domain Prefiltering for Single-Carrier Spatial Modulation Systems." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/6w3yu4.

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碩士<br>國立成功大學<br>電腦與通信工程研究所<br>106<br>Combating inter-antenna interference (IAI) and inter-symbol interference (ISI) caused by multipath channels is a very important issue in single-carrier spatial modulation (SC-SM) systems. Although using linear equalizers achieves a low complexity, the bit–error-rate (BER) performance is far from optimal. The maximum likelihood detector (MLD) gives the optimal BER performance; however, the complexity increases exponentially with a larger constellation size or a longer data block length. Taking advantage of the block circulant characteristic of the channel in the SC-SM systems, the M-algorithm can be directly applied to reduce the complexity of the MLD. Due to the fading channels, however, this method needs to retain a large number of branches to maintain a good BER performance, which results in a high complexity in tree search. In the thesis, we propose to precede the M-algorithm with an appropriately designed frequency-domain prefilter to improve the equivalent channel, so that the number of branches retained by the M-algorithm (and thus the complexity of tree search) can be significantly reduced. Since the signal processing and design of the prefilter are done in the frequency domain, the complexity overhead incurred by prefiltering is relatively small. Simulation results demonstrate that compared to the conventional M-algorithm, the proposed algorithm achieves the same BER performance with a considerably lower complexity

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Books on the topic "Prefiltering"

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McDarby, Gareth. Prefiltering and adaptive equalisation for GSM. University College Dublin, 1995.

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2

Fargues, Monique P. TLS-based prefiltering technique for time-domain ARMA modeling. Naval Postgraduate School, 1994.

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3

Geological Survey (U.S.). National Mapping Division, ed. Examples of constrained iterative restoration of SPOT panchromatic images, with prefiltering for noise reduction. U.S. Dept. of the Interior, U.S. Geological Survey, National Mapping Division, 1994.

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Book chapters on the topic "Prefiltering"

1

Sismis, Lukas, and Jan Korenek. "Analysis of TLS Prefiltering for IDS Acceleration." In Passive and Active Measurement. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28486-1_5.

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2

Lundmark, Astrid, and Leif Haglund. "Adaptive Spatial and Temporal Prefiltering for Video Compression." In Image Analysis. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_125.

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Delibasis, K., S. V. Georgakopoulos, S. K. Tasoulis, I. Maglogiannis, and V. P. Plagianakos. "On Image Prefiltering for Skin Lesion Characterization Utilizing Deep Transfer Learning." In Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48791-1_29.

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Liu, Tingwen, Yong Sun, Alex X. Liu, Li Guo, and Binxing Fang. "A Prefiltering Approach to Regular Expression Matching for Network Security Systems." In Applied Cryptography and Network Security. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31284-7_22.

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Ziliani, Francesco, and Julien Reichel. "Second Generation Prefiltering for Video Compression and Analysis in Multisensor Surveillance Systems." In Multisensor Surveillance Systems. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0371-2_7.

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Melchior, P., and S. Victor. "Fractional Approaches in Path Tracking Design (or Motion Control): Prefiltering, Shaping, and Flatness." In Intelligent Systems, Control and Automation: Science and Engineering. Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9807-5_5.

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Thapar, Pooja, and Lalit Sen Sharma. "Implementing SPARQL-Based Prefiltering on Jena Fuseki TDB Store to Reduce the Semantic Web Services Search Space." In Evolutionary Computing and Mobile Sustainable Networks. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9605-3_22.

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Garcia, Y., C. Franco, and C. J. Miosso. "Method for Improved Image Reconstruction in Computed Tomography and Positron Emission Tomography, Based on Compressive Sensing with Prefiltering in the Frequency Domain." In XXVII Brazilian Congress on Biomedical Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-70601-2_295.

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Tong, Howell. "Case studies." In Non-linear Time Series. Oxford University PressOxford, 1990. http://dx.doi.org/10.1093/oso/9780198522249.003.0007.

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Abstract Although systematic studies of non-linear time series modelling are fairly recent activities, non-linearity has been recognized for quite a considerable time. In the past, a popular approach was first to pass the data through a simple non-linear filter (e.g. a limiter; cf. the hard censoring device of §3.3.2) and then the filtered data could be modelled by a linear model. This is somewhat similar in spirit to the pre-whitening approach advocated by Tukey in the 1950s in spectral analysis (see e.g. Priestley 1981, p. 556). An early example of successful application of this prefiltering approach to non-linear time series modelling was in control engineering (see e.g. Otomo et al. 1972).

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Yang, Fan, and Michel Paindavoine. "Prefiltering for pattern recognition using wavelet transform and neural networks." In Advances in Imaging and Electron Physics. Elsevier, 2003. http://dx.doi.org/10.1016/s1076-5670(03)80098-8.

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Conference papers on the topic "Prefiltering"

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De Giusti, Andrea, and Matteo Romanin. "Speech Dereverberation Using U-Net and Minimum-Phase Inverse Prefiltering." In 2024 32nd Telecommunications Forum (TELFOR). IEEE, 2024. https://doi.org/10.1109/telfor63250.2024.10819100.

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Laczko, P., B. Feher, and B. Benyo. "FPGA-based BLAST prefiltering." In 2010 IEEE 14th International Conference on Intelligent Engineering Systems (INES 2010). IEEE, 2010. http://dx.doi.org/10.1109/ines.2010.5483825.

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Wang, Ling, and Xiang Feng. "Prefiltering of Multiwavelet with Banlancing." In 2006 International Conference on Machine Learning and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icmlc.2006.258874.

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Hervet, Eric, Cedric Lemarechal, Philippe Marthon, Y. Belgued, and Armand Lopes. "SAR image registration without prefiltering." In Remote Sensing, edited by Francesco Posa. SPIE, 1999. http://dx.doi.org/10.1117/12.373156.

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Greenhalgh, Philip A., Robin D. Abel, and Phillip A. Davies. "Optical prefiltering in subcarrier systems." In Fibers '92, edited by Andrew R. Pirich and Paul Sierak. SPIE, 1993. http://dx.doi.org/10.1117/12.141702.

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Hadar, Ofer, and Adrian Stern. "Image compression improvement by prefiltering." In SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, edited by Andrew G. Tescher. SPIE, 1998. http://dx.doi.org/10.1117/12.323160.

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Motłoch, Szymon, Mateusz Szczygielski, and Grzegorz Sarwas. "Image Prefiltering in DeepFake Detection." In 17th International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0010841200003124.

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Cusmuliuc, Ciprian-Gabriel, Stefan Claudiu Susan, Bianca Demetra Chirica, and Adrian Iftene. "News identification metric for classification prefiltering." In 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA). IEEE, 2021. http://dx.doi.org/10.1109/inista52262.2021.9548590.

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Huang, Chia-Hsin, Tyng-Ruey Chuang, and Hahn-Ming Lee. "Prefiltering techniques for efficient XML document processing." In the 2005 ACM symposium. ACM Press, 2005. http://dx.doi.org/10.1145/1096601.1096641.

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Koch, Christoph, Stefanie Scherzinger, and Michael Schmidt. "XML Prefiltering as a String Matching Problem." In 2008 IEEE 24th International Conference on Data Engineering (ICDE 2008). IEEE, 2008. http://dx.doi.org/10.1109/icde.2008.4497471.

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