Issue |
J. Space Weather Space Clim.
Volume 6, 2016
Statistical Challenges in Solar Information Processing
|
|
---|---|---|
Article Number | A16 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/swsc/2016010 | |
Published online | 08 March 2016 |
- Agrawal, J., and S. Agrawal. Acceleration based Particle Swarm Optimization (APSO) for RNA secondary structure prediction, Progress in Systems Engineering, Volume 330 of the series Advances in Intelligent Systems and Computing, Springer International Publishing, Switzerland,, 741–746, 2015, DOI: 10.1007/978-3-319-08422-0_106. [CrossRef] [Google Scholar]
- Amini, A., S. Tehrani, and T.E. Weymouth. Using dynamic programming for minimizing the energy of active contours in the presence of hard constraints, Second International Conference on Computer Vision, Tampa, FL, 95–99, 1988, DOI: 10.1109/CCV.1988.589976. [Google Scholar]
- Asl, M.A., and S.A. Seyedin. Active Contour Optimization Using Particle Swarm Optimizer, 2nd International Conference on Information & Communication Technologies, Damascus, 1, 522–523, 2006, DOI: 10.1109/ICTTA.2006.1684608. [Google Scholar]
- Ballerini, L. Genetic snakes for medical images segmentation. Evolutionary Image Analysis, Signal Processing and Telecommunications, 1596, 59–73, 1999, DOI: 10.1007/10704703_5. [CrossRef] [Google Scholar]
- Ballerini, L., and L. Bocchi. Multiple genetic snakes for bone segmentation, Applications of Evolutionary Computing, Essex, UK, 346–356, 2003, DOI: 10.1007/3-540-36605-9_32. [Google Scholar]
- Brajša, R., H. Wöhl, V. Ruždjak, F. Clette, and J.F. Hochedez. Solar differential rotation determined by tracing coronal bright points in SOHO-EIT images I. Interactive and automatic methods of data reduction. A&A, 374, 309–315, 2001, DOI: 10.1051/0004-6361:20010694. [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Brajša, R., D. Sudar, I. Skokić, and S.H. Saar. Preliminary results on the solar rotation determined tracing SDO/AIA coronal bright points. Cent. Eur. Aphys. Bull., 38, 105–110, 2014. [Google Scholar]
- Brajša, R., H. Wöhl, B. Vršnak, V. Ruždjak, F. Clette, J.F. Hochedez, and D. Roša. Height correction in the measurement of solar differential rotation determined by coronal bright points. A&A, 414, 707–715, 2004, DOI: 10.1051/0004-6361:20034082. [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Bresson, X., S. Esedoḡlu, P. Vandergheynst, J.P. Thiran, and S. Osher. Fast global minimization of the active contour/snake model. J. Math. Imaging Vis., 28, 151–167, 2007, DOI: 10.1007/s10851-007-0002-0. [CrossRef] [Google Scholar]
- Brown, D.S., C.E. Parnell, E.E. Deluca, L. Golub, and R.A. McMullen. The magnetic structure of a coronal X-ray bright point. Sol. Phys., 201, 305–321, 2001, DOI: 10.1023/A:1017907406350. [NASA ADS] [CrossRef] [Google Scholar]
- Caselles, V., R. Kimmel, and G. Sapiro. Geodesic active contours. Int. J. Comput. Vision, 22, 61–79, 1997, DOI: 10.1023/A:1007979827043. [CrossRef] [Google Scholar]
- Cohen, L.D., and I. Cohen. Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Trans. Pattern Anal. Mach. Intell., 15, 1131–1147, 1993, DOI: 10.1109/34.244675. [CrossRef] [Google Scholar]
- Davatzikos, C., and J.L. Prince. Convexity analysis of active contour models, Proc. Conf. Info. Sci. Sys., Princeton, NJ, 581–587, 1994. [Google Scholar]
- Eberhart, R.C., and Y. Shi. Tracking and optimizing dynamic systems with particle swarms, Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, 94–97, 2001, DOI: 10.1109/CEC.2001.934376. [Google Scholar]
- Eberhart, R.C., and X. Hu. Human tremor analysis using particle swarm optimization, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, Washington, DC, 3, 1999, DOI: 10.1109/CEC.1999.785508. [Google Scholar]
- Ethni, S.A., B. Zahawi, D. Giaouris, and P.P. Acarnley. Comparison of particle swarm and simulated annealing algorithms for induction motor fault identification, IEEE International Conference on Industrial Informatics (INDIN), Cardiff, Wales, 470–474, 2009, DOI: 10.1109/INDIN.2009.5195849. [Google Scholar]
- Habbal, S.R., and G.L. Withbroe. Spatial and temporal variations of EUV coronal bright points. Sol. Phys., 69, 77–97, 1981, DOI: 10.1007/BF00151257. [NASA ADS] [CrossRef] [Google Scholar]
- Habib, S.J., and B.S. Al-kazemi. Comparative study between the internal behavior of GA and PSO through problem-specific distance functions, IEEE Congress on Evolutionary Computation, Edinburgh, Scotland, UK, 2005, DOI: 10.1109/CEC.2005.1554966. [Google Scholar]
- Hanasoge, S., M.S. Miesch, M. Roth, J. Schou, and M.J. Thompson. Solar dynamics, rotation, convection and overshoot. Space Sci. Rev., 196, 79–99, 2015, DOI: 10.1007/s11214-015-0144-0. [Google Scholar]
- Hara, H. Differential rotation rate of X-ray bright points and source region of their magnetic fields. Astrophys. J., 697, 980, 2009, DOI: 10.1088/0004-637X/697/2/980. [NASA ADS] [CrossRef] [Google Scholar]
- Hassan, R., B.E. Cohanim, O.L. de Weck, and G. Venter. A comparison of particle swarm optimization and the genetic algorithm, Proceedings of the 1st AIAA Multidisciplinary Design Optimization Specialist Conference, Austin, Texas, American Institute of Aeronautics and Astronautics, 2005, DOI: 10.2514/6.2005-1897. [Google Scholar]
- He, N., P. Zhang, and K. Lu. A geometric active contours model for multiple objects segmentation, Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues, Springer-Verlag, Berlin Heidelberg, 1141–1148, 2008, DOI: 10.1007/978-3-540-87442-3_141. [CrossRef] [Google Scholar]
- Holden, N., and A.A. Freitas. Hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data, Proc. IEEE Int. Symp. Swarm Intelligence, Pasadena, CA, USA, 100–107, 2005, DOI: 10.1109/SIS.2005.1501608. [Google Scholar]
- Hoos, H.H., and T. Stützle. Stochastic Local Search: Foundations & Applications, Elsevier, San Francisco, CA, 2004. [Google Scholar]
- Horng, M.H., R.J. Liou, and J. Wu. Parametric active contour model by using the honey bee mating optimization. Expert Syst. Appl., 37, 7015–7025, 2010, DOI: 10.1016/j.eswa.2010.03.017. [CrossRef] [Google Scholar]
- Howard, R. Solar rotation. Ann. Rev. Astron. Astrophys., 22, 131–155, 1984, DOI: 10.1146/annurev.aa.22.090184.001023. [Google Scholar]
- Howard, R., and J. Harvey. Spectroscopic determinations of solar rotation. Sol. Phys., 12, 23–51, 1970, DOI: 10.1007/BF02276562. [NASA ADS] [CrossRef] [Google Scholar]
- Howard, R., and B.J. LaBonte. The Sun is observed to be a torsional oscillator with a period of 11 years. Astrophys. J., 239, L33–36, 1980. [Google Scholar]
- Hu, X., Y. Shi, and R. Eberhart. Recent advances in particle swarm, Proceedings of the 2004 Congress on Evolutionary Computation, Portland, OR, USA, 1, 2004, DOI: 10.1109/CEC.2004.1330842. [Google Scholar]
- Karlsson, A., K. Stråhlén, and A. Heyden. A fast snake segmentation method applied to histopathological sections, Energy Minimization Methods in Computer Vision and Pattern Recognition, Lisbon, Portugal, 261–274, 2003, DOI: 10.1007/978-3-540-45063-4_17. [Google Scholar]
- Kass, M., A. Witkin, and D. Terzopoulos. Snakes: active contour models. Int. J. Comput. Vision, 1, 321–331, 1988, DOI: 10.1007/BF00133570. [Google Scholar]
- Kennedy, J., and R. Eberhart. Particle swarm optimization, IEEE International Conference on Neural Networks, Perth, WA, 4, 1942–48, 1995, DOI: 10.1109/ICNN.1995.488968. [Google Scholar]
- Lam, K.M., and H. Yan. Fast Greedy algorithm for active contours. Electron. Lett., 30, 21–23, 1994, DOI: 10.1049/el:19940040. [CrossRef] [Google Scholar]
- Lemen, J.R., D.J. Akin, P.F. Boerner, C. Chou, J.F. Drake, et al. The Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO). Sol. Phys., 275, 17–40, 2012, DOI: 10.1007/s11207-011-9776-8. [NASA ADS] [CrossRef] [Google Scholar]
- Leroy, B., I.L. Herlin, and L.D. Cohen. Multi-resolution algorithms for active contour models. ICAOS’96, 219, 58–65, 1996, DOI: 10.1007/3-540-76076-8_117. [Google Scholar]
- Li, B., and S.T. Acton. Active contour external force using vector field convolution for image segmentation. IEEE Trans. Image Process., 16, 2096–2106, 2007, DOI: 10.1109/TIP.2007.899601. [CrossRef] [Google Scholar]
- Li, R., Y. Guo, Y. Xing, and M. Li. A novel multi-swarm particle swarm optimization algorithm applied in active contour model, WRI Global Congress on Intelligent Systems, GCIS ‘09, 139–143, 2009, DOI: 10.1109/GCIS.2009.57. [Google Scholar]
- Lorenc, M., M. Rybanský, and I. Dorotovič. On rotation of the solar corona. Sol. Phys., 281, 611–619, 2012, DOI: 10.1007/s11207-012-0105-7. [NASA ADS] [CrossRef] [Google Scholar]
- Marinakis, Y., M. Marinaki, and G. Dounias. A hybrid particle swarm optimization algorithm for the vehicle routing problem. Eng. Appl. Artif. Intell., 23, 463–472, 2010, DOI: 10.1016/j.engappai.2010.02.002. [CrossRef] [Google Scholar]
- McInerney, T., and D. Terzopoulos. Deformable models in medical image analysis: a survey. Med. Image Anal., 1, 91–108, 1996, DOI: 10.1016/S1361-8415(96)80007-7. [CrossRef] [Google Scholar]
- McIntosh, S.W., and J.B. Gurman. Nine years of EUV bright points. Sol. Phys., 228, 285–299, 2005, DOI: 10.1007/s11207-005-4725-z. [NASA ADS] [CrossRef] [Google Scholar]
- Mun, K.J., H.T. Kang, H.S. Lee, Y.S. Yoon, C.M. Lee, and J.H. Park. Active contour model based object contour detection using genetic algorithm with wavelet based image preprocessing. Int. J. Control Autom. Syst., 2, 100–106, 2004. [Google Scholar]
- Nebti, S., and S. Meshoul. Predator prey optimization for snake-based contour detection. International Journal of Intelligent Computing and Cybernetics, 2, 228–242, 2009, DOI: 10.1108/17563780910959884. [CrossRef] [Google Scholar]
- Niu, X. A geometric active contour model for highway extraction, Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada, 2006. [Google Scholar]
- Panda, S., and N.P. Padhy. Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design. Applied Soft Computing, 8, 1418–1427, 2008, DOI: 10.1016/j.asoc.2007.10.009. [CrossRef] [Google Scholar]
- Paragios, N., and R. Deriche. Geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Trans. Pattern Anal. Mach. Intell., 22, 266–280, 2000, DOI: 10.1109/34.841758. [CrossRef] [Google Scholar]
- Park, H.W., T. Schoepflin, and Y. Kim. Active contour model with gradient directional information: directional snake. IEEE Trans. Circuits Syst. Video Technol., 11, 252–256, 2001, DOI: 10.1109/76.905991. [CrossRef] [Google Scholar]
- Peli, E. Contrast in complex images. J. Opt. Soc. Am., A7, 2032–2040, 1990, DOI: 10.1364/JOSAA.7.002032. [CrossRef] [Google Scholar]
- Pesnell, W.D., B.J. Thompson, and P.C. Chamberlin. The Solar Dynamics Observatory (SDO). Sol. Phys., 275, 3–15, 2012, DOI: 10.1007/s11207-011-9841-3. [NASA ADS] [CrossRef] [Google Scholar]
- Poli, R. Analysis of the publications on the applications of particle swarm optimisation. JAEA, 2008, 1–10, 2008, DOI: 10.1155/2008/685175. [Google Scholar]
- Prince, J.L. Gradient vector flow: a new external force for snakes. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, 2, 66–71, 1997, DOI: 10.1109/CVPR.1997.609299. [Google Scholar]
- Ram, G., D. Mandal, R. Kar, and S.P. Ghosal. Synthesis of time modulated linear antenna arrays using particle swarm optimization, IEEE Region 10 Conference, TENCON’14, Bangkok, 1–4, 2014, DOI: 10.1109/TENCON.2014.7022315. [Google Scholar]
- Robinson, J., S. Sinton, and Y. Rahmat-Samii. Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna, IEEE Antennas and Propagation Society International Symposium, 314–317, 2002, DOI: 10.1109/APS.2002.1016311. [Google Scholar]
- Scherrer, P.H., J. Schou, R.I. Bush, A.G. Kosovichev, R.S. Bogart, et al. The Helioseismic and Magnetic Imager (HMI) investigation for the Solar Dynamics Observatory (SDO), The Solar Dynamics Observatory, Springer, US, 207–227, 2011, DOI: 10.1007/978-1-4614-3673-7_10. [CrossRef] [Google Scholar]
- Shahamatnia, E., I. Dorotovič, R.A. Ribeiro, and J.M. Fonseca. Towards an automatic sunspot tracking: swarm intelligence and snake model hybrid. Acta Futura, 5, 153–61, 2012, DOI: 10.2420/AF05.2012.153. [Google Scholar]
- Shahamatnia, E., and M.M. Ebadzadeh. Application of particle swarm optimization and snake model hybrid on medical imaging, IEEE Third International Workshop on Computational Intelligence In Medical Imaging, Paris, France, 2011, DOI: 10.1109/CIMI.2011.5952043. [Google Scholar]
- Sudar, D., I. Skokic, R. Brajša, and H. Saar. Steps toward a high precision solar rotation profile: results from SDO/AIA coronal bright point data. A&A, 575, A63, 2015, DOI: 10.1051/0004-6361/201424929. [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Thompson, M.J., J. Toomre, E.R. Anderson, H.M. Antia, G. Berthomieu, et al. Differential rotation and dynamics of the solar interior. Science, 272, 1300–1305, 1996, DOI: 10.1126/science.272.5266.1300. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
- Trelea, I.C. The particle swarm optimization algorithm: convergence analysis and parameter selection. Inform. Process. Lett., 85, 317–325, 2003, DOI: 10.1016/S0020-0190(02)00447-7. [Google Scholar]
- Tseng, C.C., J. Hsieh, and J. Jeng. Active contour model via multi-population particle swarm optimization. Expert Syst. Appl., 36, 5348–5352, 2009, DOI: 10.1016/j.eswa.2008.06.114. [CrossRef] [Google Scholar]
- Van den Bergh, F. An analysis of particle swarm optimizers, Ph.D. dissertation, University of Pretoria, 2002. [Google Scholar]
- Wildenauer, H., P. Blauensteiner, A. Hanbury, and M. Kampel. Motion detection using an improved colour model, Advances in Visual Computing, Springer, Berlin Heidelberg, 607–616, 2006, DOI: 10.1007/11919629_61. [Google Scholar]
- Wöhl, H., R. Brajša, A. Hanslmeier, and S.F. Gissot. A precise measurement of the solar differential rotation by tracing small bright coronal structures in SOHO-EIT images. A&A, 520, A29, 2010, DOI: 10.1051/0004-6361/200913081. [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Xu, C., and J.L. Prince. Snakes, shapes, and gradient vector flow. IEEE Trans. Image Process., Pacific Grove, CA, USA, 7, 359–369, 1998, DOI: 10.1109/83.661186. [Google Scholar]
- Xu, C., A. Yezzi, and J.L. Prince. On the relationship between parametric and geometric active contours, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers, 1, 483–489, 2000, DOI: 10.1109/ACSSC.2000.911003. [Google Scholar]
- Yang, X.S., Editor. Recent Advances in Swarm Intelligence and Evolutionary Computation, 1st ed., Vol. 585, Springer International Publishing, Switzerland, 2015, DOI: 10.1007/978-3-319-13826-8. [Google Scholar]
- Yang, F., C. Zhang, and T. Sun. Comparison of particle swarm optimization and genetic algorithm for HMM training, 19th International Conference on Pattern Recognition, Tampa, FL, 2008, DOI: 10.1109/ICPR.2008.4761282. [Google Scholar]
- Zeng, D., and Z. Zhou. Invariant topology snakes driven by particle swarm optimizer, 3rd International Conference on Innovative Computing Information and Control, Dalian, Liaoning, 38–38, 2008, DOI: 10.1109/ICICIC.2008.332. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.