A novel ship classification approach for high resolution SAR images based on the BDA-KELM classification model

References

• Andrew, A. M. 2001. “An Introduction to Support Vector Machines and Other Kernel‐Based Learning Methods.” Kybernetes 32 (1): 1–28.
   Google Scholar
• Chen, H. L., G. Wang, C. Ma, Z. N. Cai, W. B. Liu, and S. J. Wang. 2016. “An Efficient Hybrid Kernel Extreme Learning Machine Approach for Early Diagnosis of Parkinson’s Disease.” Neurocomputing 184 (4745): 131–144. doi:10.1016/j.neucom.2015.07.138.
   Web of Science ®Google Scholar
• Chen, W. T., K. F. Ji, X. W. Xing, and H. X. Zou. 2012. “Ship Recognition in High Resolution SAR Imagery Based on Feature Selection”. International Conference on Computer Vision in Remote Sensing, Xianmen. 301–305. doi:10.1109/CVRS.2012.6421279
   Google Scholar
• Ding, S., J. Zhang, X. Xu, and Y. Zhang. 2016. “A Wavelet Extreme Learning Machine.” Neural Computing and Applications 27 (4): 1033–1040. doi:10.1007/s00521-015-1918-8.
   Web of Science ®Google Scholar
• Ding, S., Y. Zhang, X. Xinzheng, and L. Bao. 2013. “A Novel Extreme Learning Machine Based on Hybrid Kernel Function.” Journal of Computers No 8 (8): 2110–2117.
   Google Scholar
• Feng, D., C. Yang, A. Xiao, C. Ruan, and H. Zhang. 2010. “Module Partition Research for the Marine Drilling Rig.” Advanced Materials Research No 160-162: 440–445. doi:10.4028/www.scientific.net/AMR.160-162.
   Google Scholar
• Gagnon, L. 1997. “Classification of Ships in Airborne SAR Imagery Using Backpropagation Neural Networks”. SPIE Meeting: Radar Processing, Technology and Applications II, CiteSeer. 126–136. doi:10.1117/12.279464.
   Google Scholar
• Guyon, I., and A. Elisseeff. 2002. “An Introduction to Variable and Feature Selection.” Journal of Machine Learning Research 3 (6): 1157–1182.
   Google Scholar
• Huang, G. B., L. Chen, and C. K. Siew. 2006. “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes.” IEEE Transactions on Neural Networks 17 (4): 879–892. doi:10.1109/TNN.2006.875977.
   PubMed Web of Science ®Google Scholar
• Huang, G. B., Q. Y. Zhu, and C. K. Siew. 2004. “Extreme Learning Machine: A New Learning Scheme of Feedforward Neural Networks.” Proc.Int.Joint Conf.Neural Netw 2: 985–990.
   Google Scholar
• Huang, G. B., Q. Y. Zhu, and C. K. Siew. 2006. “Extreme Learning Machine: Theory and Applications.” Neurocomputing 70 (1–3): 489–501. doi:10.1016/j.neucom.2005.12.126.
   Web of Science ®Google Scholar
• Jangir, P., R. H. Bhesdadiya, M. H. Pandya, I. N. Trivedi, N. Jangir, and A. Kumar. 2016. “Price Penalty Factors Based Approach for Combined Economic Emission Dispatch Problem Solution Using Dragonfly Algorithm”. International Conference on Energy Efficient Technologies for Sustainability IEEE, Nagercoil, India. doi:10.1109/ICEETS.2016.7583794
   Google Scholar
• Ji, K., X. Xing, W. Chen, and H. Zou. 2013. “Ship Classification in TerraSAR-X SAR Images Based on Classifier Combination”. Paper read at Geoscience and Remote Sensing Symposium, Melbourne, VIC. 2589–2592. doi:10.1109/IGARSS.2013.6723352.
   Google Scholar
• Jiang, M., X. Yang, Z. Dong, and S. Fang. 2016. “Ship Classification Based on Superstructure Scattering Features in SAR Images.” IEEE Geoscience & Remote Sensing Letters 13 (5): 616–620. doi:10.1109/LGRS.2016.2514482.
   Web of Science ®Google Scholar
• Kira, K., and L. A. Rendell. 1992. “The Feature Selection Problem: Traditional Methods and a New Algorithm”. Paper read at Tenth National Conference on Artificial Intelligence, San Jose, CA. 129–134 .
   Google Scholar
• Kohavi, R., and G. H. John. 1997. “Wrappers for Feature Subset Selection.” Artificial Intelligence 97 (1–2): 273–324. doi:10.1016/S0004-3702(97)00043-X.
   Web of Science ®Google Scholar
• Lang, H., J. Zhang, X. Zhang, and J. Meng. 2015. “Ship Classification in SAR Image by Joint Feature and Classifier Selection.” IEEE Geoscience & Remote Sensing Letters 13 (2): 1–5.
   Web of Science ®Google Scholar
• Liang, N. Y., G. B. Huang, P. Saratchandran, and N. Sundararajan. 2006. “A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks.” IEEE Transactions on Neural Networks 17 (6): 1411–1423. doi:10.1109/TNN.2006.880583.
   PubMed Web of Science ®Google Scholar
• Liu, C., P. W. Vachon, and G. W. Geling. 2005. “Improved Ship Detection with Airborne Polarimetric SAR Data.” Canadian Journal of Remote Sensing Journal Canadien De Télédétection 31 (1): 122–131. doi:10.5589/m04-056.
   Web of Science ®Google Scholar
• Margarit, G., J. J. Mallorqui, J. Fortuny-Guasch, and C. Lopez-Martinez. 2009. “Exploitation of Ship Scattering in Polarimetric SAR for an Improved Classification under High Clutter Conditions.” IEEE Transactions on Geoscience & Remote Sensing 47 (4): 1224–1235. doi:10.1109/TGRS.2008.2008721.
   Web of Science ®Google Scholar
• Margarit, G., and A. Tabasco. 2011. “Ship Classification in Single-Pol SAR Images Based on Fuzzy Logic.” IEEE Transactions on Geoscience & Remote Sensing 49 (8): 3129–3138. doi:10.1109/TGRS.2011.2112371.
   Web of Science ®Google Scholar
• Mirjalili, S. 2016. “Dragonfly Algorithm: A New Meta-Heuristic Optimization Technique for Solving Single-Objective, Discrete, and Multi-Objective Problems.” Neural Computing and Applications 27 (4): 1053–1073. doi:10.1007/s00521-015-1920-1.
   Web of Science ®Google Scholar
• Pal, M., A. E. Maxwell, and T. A. Warner. 2013. “Kernel-Based Extreme Learning Machine for Remote-Sensing Image Classification.” Remote Sensing Letters 4 (9): 853–862. doi:10.1080/2150704X.2013.805279.
   Web of Science ®Google Scholar
• Peng, H., F. Long, and C. Ding. 2005. “Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy.” IEEE Transactions on Pattern Analysis & Machine Intelligence 27 (8): 1226–1238. doi:10.1109/TPAMI.2005.159.
   PubMed Web of Science ®Google Scholar
• Pilcher, C. M., and A. Khotanzad. 2011. “Maritime ATR Using Classifier Combination and High Resolution Range Profiles.” IEEE Transactions on Aerospace & Electronic Systems 47 (4): 2558–2573. doi:10.1109/TAES.2011.6034651.
   Web of Science ®Google Scholar
• Raman, G., G. Raman, C. Manickam, and S. I. Ganesan. 2016. “Dragonfly Algorithm Based Global Maximum Power Point Tracker for Photovoltaic Systems.” Advances in Swarm Intelligence.
   Google Scholar
• Tang, J., S. Alelyani, and H. Liu. 1993. “Feature Selection for Classification: A Review.” Documentación Administrativa 313–334.
   Google Scholar
• Valin, P., Y. Tessier, and A. Jouan. 1999. “Hierarchical Ship Classifier for Airborne Synthetic Aperture Radar (SAR) Images”. Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020), Pacific Grove, CA. 2: 1230–1234.
   Google Scholar
• Velotto, D., and S. Lehner. 2014. “On the Use of Full Polarimetric SAR Data to Remove Azimuth Ambiguity: Application Ship Detection”. Proceedings of European Conference on Synthetic Aperture Radar, Berlin, Germany. 1–4.
   Google Scholar
• Wang, C., H. Zhang, F. Wu, S. Jiang, B. Zhang, and Y. Tang. 2014. “A Novel Hierarchical Ship Classifier for COSMO-SkyMed SAR Data.” IEEE Geoscience & Remote Sensing Letters 11 (2): 484–488. doi:10.1109/LGRS.2013.2268875.
   Web of Science ®Google Scholar
• Xing, X., J. Kefeng, H. Zou, and W. Chen. 2013. “Ship Classification in TerraSAR-X Images with Feature Space Based Sparse Representation.” IEEE Geoscience & Remote Sensing Letters 10 (6): 1562–1566. doi:10.1109/LGRS.2013.2262073.
   Web of Science ®Google Scholar
• Xing, X. W., K. F. Ji, W. T. Chen, H. X. Zou, and J. X. Sun. 2014. “Superstructure Scattering Distribution Based Ship Recognition in TerraSAR-X Imagery.” IOP Conference Series: Earth and Environmental Science 17: 682–691.
   Google Scholar
• Xiong, Z., and Z. Jie. 2004. “Modelling and Optimal Control of Fed-Batch Processes Using a Novel Control Affine Feedforward Neural Network.” Neurocomputing 61 (2): 317–337.
   Web of Science ®Google Scholar
• Yeremy, M., J. W. M. Campbell, K. Mattar, and T. Potter. 2014. “Ocean Surveillance with Polarimetric SAR.” Canadian Journal of Remote Sensing 27 (4): 328–344. doi:10.1080/07038992.2001.10854875.
   Web of Science ®Google Scholar
• Zawbaa, H. M., E. Emary, M. Abdul Salam, K. K. A. Ghany, and B. Parv. 2016. “A Hybrid Dragonfly Algorithm with Extreme Learning Machine for Prediction”. International Symposium on INnovations in Intelligent SysTems and Applications (INISTA), Sinaia, Romania. 1–6.
   Google Scholar
• Zhang, X., J. Zhang, J. I. Yong-Gang, and J. M. Meng. 2010. “The Capability Analysis of Ship Classification by Structure Feature Using SAR Images.” Acta Oceanologica Sinica.
   Google Scholar
• Zhang, Y., S. Ding, X. Xinzheng, H. Zhao, and W. Xing. 2013. “An Algorithm Research for Prediction of Extreme Learning Machines Based on Rough Sets.” Journal of Computers 8 (5): 1335–1342.
   Google Scholar