Academic literature on the topic 'Iterative enhancement'
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Journal articles on the topic "Iterative enhancement"
LI, Chao-you, and Ji-zhou SUN. "Fingerprint image fusion iterative enhancement." Journal of Computer Applications 31, no. 6 (April 9, 2012): 1563–65. http://dx.doi.org/10.3724/sp.j.1087.2011.01563.
Full textA Nazren, A. R., Ngadiran R., and S. N. Yaakob. "Edge enhancement of IBP reconstruction by using sharp infinite symmetrical exponential filter." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 1 (April 1, 2019): 258. http://dx.doi.org/10.11591/ijeecs.v14.i1.pp258-266.
Full textKrylov, A. S., A. V. Nasonova, and A. A. Nasonov. "Image enhancement by non-iterative grid warping." Pattern Recognition and Image Analysis 26, no. 1 (January 2016): 161–64. http://dx.doi.org/10.1134/s1054661816010132.
Full textMonk, Timothy A., Paul J. Hurst, and Stephen H. Lewis. "Iterative Gain Enhancement in an Algorithmic ADC." IEEE Transactions on Circuits and Systems I: Regular Papers 63, no. 4 (April 2016): 459–69. http://dx.doi.org/10.1109/tcsi.2016.2528081.
Full textDas, Amit, and John H. L. Hansen. "Constrained Iterative Speech Enhancement Using Phonetic Classes." IEEE Transactions on Audio, Speech, and Language Processing 20, no. 6 (August 2012): 1869–83. http://dx.doi.org/10.1109/tasl.2012.2191282.
Full textWeinstein, E., A. V. Oppenheim, M. Feder, and J. R. Buck. "Iterative and sequential algorithms for multisensor signal enhancement." IEEE Transactions on Signal Processing 42, no. 4 (April 1994): 846–59. http://dx.doi.org/10.1109/78.285648.
Full textGÁSPÁR, PÉTER, LÁSZLÓ PALKOVICS, and J. ÓZSEF BOKOR. "ITERATIVE DESIGN OF VEHICLE COMBINATIONS FOR STABILITY ENHANCEMENT." Vehicle System Dynamics 29, sup1 (January 1998): 451–61. http://dx.doi.org/10.1080/00423119808969578.
Full textHutchens, David H., and Elizabeth E. Katz. "Using iterative enhancement in undergraduate software engineering courses." ACM SIGCSE Bulletin 28, no. 1 (March 1996): 266–70. http://dx.doi.org/10.1145/236462.236553.
Full textJensen, J., and J. H. L. Hansen. "Speech enhancement using a constrained iterative sinusoidal model." IEEE Transactions on Speech and Audio Processing 9, no. 7 (2001): 731–40. http://dx.doi.org/10.1109/89.952491.
Full textWindmann, Stefan, and Reinhold Haeb-Umbach. "Approaches to Iterative Speech Feature Enhancement and Recognition." IEEE Transactions on Audio, Speech, and Language Processing 17, no. 5 (July 2009): 974–84. http://dx.doi.org/10.1109/tasl.2009.2014894.
Full textDissertations / Theses on the topic "Iterative enhancement"
Das, Amit. "Rover based constrained iterative speech enhancement." Connect to online resource, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1442925.
Full textSunnegårdh, Johan. "Iterative Enhancement of Non-Exact Reconstruction in Cone Beam CT." Thesis, Computer Vision, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2577.
Full textContemporary algorithms employed for reconstruction of 3D volumes from helical cone beam projections are so called non-exact algorithms. This means that the reconstructed volumes will contain artifacts irrespective of the detector resolution and number of projections angles employed in the process.
It has been proposed that these artifacts can be suppressed using an iterative scheme which comprises computation of projections from the already reconstructed volume as well as the non-exact reconstruction itself.
The purpose of the present work is to examine if the iterative scheme can be applied to the non-exact reconstruction method PI-original in order to improve the reconstruction result. An important part in this implementation is a careful design of the projection operator, as a poorly designed projection operator may result in aliasing and/or other artifacts in the reconstruction result. Since the projection data is truncated, special care must be taken along the boundaries of the detector. Three different ways of handling this interpolation problem is proposed and examined.
The results show that artifacts caused by the PI-original method can indeed be reduced by the iterative scheme. However, each iteration requires at least three times more processing time than the initial reconstruction, which may call for certain compromises, smartness and/or parallelization in the innermost loops. Furthermore, at higher cone angles certain types of artifacts seem to grow by each iteration instead of being suppressed.
Abdul, Aziz Mohamad Kamree. "High data rate WLAN enhancement using multiple antennas and iterative processing techniques." Thesis, University of Bristol, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413619.
Full textMa, Hannan. "Iterative row-column algorithms for two-dimensional intersymbol interference channel equalization complexity reduction and performance enhancement /." Pullman, Wash. : Washington State University, 2010. http://www.dissertations.wsu.edu/Thesis/Summer2010/h_ma_062110.pdf.
Full textTitle from PDF title page (viewed on July 28, 2010). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 51).
Li, Mao Li. "Spatial-temporal classification enhancement via 3-D iterative filtering for multi-temporal Very-High-Resolution satellite images." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1514939565470669.
Full textYokota, Yusuke. "Evaluation of Image Quality of Pituitary Dynamic Contrast-Enhanced MRI Using Time-Resolved Angiography With Interleaved Stochastic Trajectories (TWIST) and Iterative Reconstruction TWIST (IT-TWIST)." Kyoto University, 2020. http://hdl.handle.net/2433/259011.
Full textWu, Zining. "Coding and iterative detection for magnetic recording channels /." Boston, Mass. [u.a.] : Kluwer Academic Publ, 2000. http://www.loc.gov/catdir/enhancements/fy0820/99049501-d.html.
Full textChappalli, Mahesh B. "Image enhancement using SGW superresolution and iterative blind deconvolution." 2005. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-985/index.html.
Full text"Visual-based decision for iterative quality enhancement in robot drawing." 2005. http://library.cuhk.edu.hk/record=b5892527.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 113-116).
Abstracts in English and Chinese.
ABSTRACT --- p.i
Chapter 1. --- INTRODUCTION --- p.1
Chapter 1.1 --- Artistic robot in western art --- p.1
Chapter 1.2 --- Chinese calligraphy robot --- p.2
Chapter 1.3 --- Our robot drawing system --- p.3
Chapter 1.4 --- Thesis outline --- p.3
Chapter 2. --- ROBOT DRAWING SYSTEM --- p.5
Chapter 2.1 --- Robot drawing manipulation --- p.5
Chapter 2.2 --- Input modes --- p.6
Chapter 2.3 --- Visual-feedback system --- p.8
Chapter 2.4 --- Footprint study setup --- p.8
Chapter 2.5 --- Chapter summary --- p.10
Chapter 3. --- LINE STROKE EXTRACTION AND ORDER ASSIGNMENT --- p.11
Chapter 3.1 --- Skeleton-based line trajectory generation --- p.12
Chapter 3.2 --- Line stroke vectorization --- p.15
Chapter 3.3 --- Skeleton tangential slope evaluation using MIC --- p.16
Chapter 3.4 --- Skeleton-based vectorization using Bezier curve interpolation --- p.21
Chapter 3.5 --- Line stroke extraction --- p.25
Chapter 3.6 --- Line stroke order assignment --- p.30
Chapter 3.7 --- Chapter summary --- p.33
Chapter 4. --- PROJECTIVE RECTIFICATION AND VISION-BASED CORRECTION --- p.34
Chapter 4.1 --- Projective rectification --- p.34
Chapter 4.2 --- Homography transformation by selected correspondences --- p.35
Chapter 4.3 --- Homography transformation using GA --- p.39
Chapter 4.4 --- Visual-based iterative correction example --- p.45
Chapter 4.5 --- Chapter summary --- p.49
Chapter 5. --- ITERATIVE ENHANCEMENT ON OFFSET EFFECT AND BRUSH THICKNESS --- p.52
Chapter 5.1 --- Offset painting effect by Chinese brush pen --- p.52
Chapter 5.2 --- Iterative robot drawing process --- p.53
Chapter 5.3 --- Iterative line drawing experimental results --- p.56
Chapter 5.4 --- Chapter summary --- p.67
Chapter 6. --- GA-BASED BRUSH STROKE GENERATION --- p.68
Chapter 6.1 --- Brush trajectory representation --- p.69
Chapter 6.2 --- Brush stroke modeling --- p.70
Chapter 6.3 --- Stroke simulation using GA --- p.72
Chapter 6.4 --- Evolutionary computing results --- p.77
Chapter 6.5 --- Chapter summary --- p.95
Chapter 7. --- BRUSH STROKE FOOTPRINT CHARACTERIZATION --- p.96
Chapter 7.1 --- Footprint video capturing --- p.97
Chapter 7.2 --- Footprint image property --- p.98
Chapter 7.3 --- Experimental results --- p.102
Chapter 7.4 --- Chapter summary --- p.109
Chapter 8. --- CONCLUSIONS AND FUTURE WORKS --- p.111
BIBLIOGRAPHY --- p.113
Su, Jian-Jhang, and 蘇建彰. "Speech Enhancement Using Iterative Wiener Filter in the Linear Predictive Model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/rf6txg.
Full text國立臺北科技大學
電機工程系研究所
100
Speech signals are tend to decrease the speech quality when corrupted by background noises. The aim of speech enhancement is to reduce the background noise from a noisy speech signal while keeping the speech distortion as low as possible. And this Speech technique is usually used in speech transmission and speech recognition that recovers the clean speech from noisy speech by using a noise tracking algorithm. There are three categories for speech enhancement including filtering techniques, spectral restoration techniques, and speech model techniques. In this thesis three speech enhancement methods based on linear predictive model are investigated that includes Kalman filter (KF), modified Kalman filter (MKF), and iterative Wiener filter (IWF). Two other famous methods the Wiener filter (WF) method and maximum-likelihood spectral amplitude (MLSA) method are also included for comparison. In the experiments, each enhancement method incorporates with three well-known noise tracking algorithms, including minimum statistics (MS), minima controlled recursive averaging (MCRA), and improved minima controlled recursive averaging (IMCRA) for recovering clean speech. The experimental results show that compared with the Wiener filter and maximum-likelihood spectral amplitude, the proposed iterative Wiener filter in the linear predictive model provides superior performance. Among all combinations, the latter with MCRA noise tracking can achieves the most excellent results.
Book chapters on the topic "Iterative enhancement"
Dickinson, Markus, and Dan Tufiş. "Iterative Enhancement." In Handbook of Linguistic Annotation, 257–76. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-0881-2_9.
Full textNaess, Ole E. "Iterative Methods for Enhancement of Multichannel Data." In Progress in Underwater Acoustics, 783–91. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1871-2_92.
Full textRakib, Md Rashadul Hasan, Norbert Zeh, Magdalena Jankowska, and Evangelos Milios. "Enhancement of Short Text Clustering by Iterative Classification." In Natural Language Processing and Information Systems, 105–17. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51310-8_10.
Full textKumar, Raj, Manoj Tripathy, and R. S. Anand. "Iterative Thresholding-Based Spectral Subtraction Algorithm for Speech Enhancement." In Advances in VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems, 221–32. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0443-0_18.
Full textKolesnik, Marina, Alexander Barlit, and Evgeny Zubkov. "Iterative Tuning of Simple Cells for Contrast Invariant Edge Enhancement." In Biologically Motivated Computer Vision, 27–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36181-2_3.
Full textSaya Nandini Devi, M., and S. Santhi. "Enhancement of Optical Coherence Tomography Images: An Iterative Approach Using Various Filters." In Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB), 107–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00665-5_12.
Full textYu, Xin, Georg Fischer, and Andreas Pascht. "Stability Enhancement of Digital Predistortion Through Stationary Iterative Methods to Solve System of Equations." In Electromagnetics and Network Theory and their Microwave Technology Applications, 263–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18375-1_19.
Full textSabbagh, L. David, Harold A. Sabbagh, and James S. Klopfenstein. "Image Enhancement via Extrapolation Techniques: A Two Dimensional Iterative Scheme a Direct Matrix Inversion Scheme." In Review of Progress in Quantitative Nondestructive Evaluation, 473–83. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4615-7763-8_49.
Full textTyagi, Manoj Kumar, Ajay Sikandar, Dheerendra Kumar Tyagi, Durgesh Kumar, Prashant Singh, Srinivasan Munisamy, and L. S. S. Reddy. "State Space Modeling of Earned Value Method for Iterative Enhancement Based Traditional Software Projects Tracking." In Communications in Computer and Information Science, 336–54. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0404-1_25.
Full textSubha Lakshmi, N., S. Allirani, S. Sundar, and H. Vidhya. "Performance Enhancement of Permanent Magnet Synchronous Motor Employing Iterative Learning Controller with Space Vector Pulse Width Modulation." In Lecture Notes in Electrical Engineering, 109–20. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7241-8_9.
Full textConference papers on the topic "Iterative enhancement"
Turroni, Francesco, Raffaele Cappelli, and Davide Maltoni. "Fingerprint enhancement using contextual iterative filtering." In 2012 5th IAPR International Conference on Biometrics (ICB). IEEE, 2012. http://dx.doi.org/10.1109/icb.2012.6199773.
Full textAlsam, Ali, Ivar Farup, and Hans Jakob Rivertz. "Iterative sharpening for image contrast enhancement." In 2015 Colour and Visual Computing Symposium (CVCS). IEEE, 2015. http://dx.doi.org/10.1109/cvcs.2015.7274891.
Full textDwivedi, Raghavnedra Kr, and Awadhesh Kr Srivastava. "Autonomic software development using iterative enhancement model." In 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT). IEEE, 2014. http://dx.doi.org/10.1109/icicict.2014.6781360.
Full textPeimin, Yan, and Wang Shuozhong. "Iterative Image Resolution Enhancement Using MAP Estimator." In 2006 9th International Conference on Control, Automation, Robotics and Vision. IEEE, 2006. http://dx.doi.org/10.1109/icarcv.2006.345395.
Full textRasti, Pejman, Hasan Demirel, and Gholamreza Anbarjafari. "Iterative back projection based image resolution enhancement." In 2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP). IEEE, 2013. http://dx.doi.org/10.1109/iranianmvip.2013.6779986.
Full textKai Zeng, B. De Man, J. B. Thibault, Zhou Yu, C. Bouman, and K. Sauer. "Spatial resolution enhancement in CT iterative reconstruction." In 2009 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2009). IEEE, 2009. http://dx.doi.org/10.1109/nssmic.2009.5401880.
Full textYohannes, Tesfay. "Image enhancement using the iterative learning approach." In Optoelectronic and Hybrid Optical/Digital Systems for Image Processing, edited by Simon B. Gurevich, Roman S. Batchevsky, and Leonid I. Muravsky. SPIE, 1997. http://dx.doi.org/10.1117/12.284785.
Full textGouhar, Tahmina, Nabih Jaber, and Pallavi Kuntumalla. "Speech enhancement using new iterative minimum statistics approach." In 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2017. http://dx.doi.org/10.1109/ccece.2017.7946768.
Full textHuimin, Zhang, Jia Xupeng, and Li Dongmei. "An Iterative Post-processing Approach for Speech Enhancement." In the 2019 4th International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3330393.3330427.
Full textHutchens, David H., and Elizabeth E. Katz. "Using iterative enhancement in undergraduate software engineering courses." In the twenty-seventh SIGCSE technical symposium. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/236452.236553.
Full text