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Articles

A segmented particle swarm optimization convolutional neural network for land cover and land use classification of remote sensing images

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Pages 1182-1191 | Received 05 Jan 2019, Accepted 15 Sep 2019, Published online: 25 Sep 2019

References

  • Chatterjee, A., and P. Siarry. 2006. “Nonlinear Inertia Weight Variation for Dynamic Adaptation in Particle Swarm Optimization.” Computers & Operations Research 33 (3): 859–871. doi:10.1016/j.cor.2004.08.012.
  • Clerc, M., and J. Kennedy. 2002. “The Particle Swarm-explosion, Stability, and Convergence in a Multidimensional Complex Space.” IEEE Trans. on Evolutionary Computantion 6 (1): 58–73. doi:10.1109/4235.985692.
  • Gao, Y., Q. Li, S. Wang, and J. Gao. 2018. “Adaptive Neural Network Based on Segmented Particle Swarm Optimization for Remote-sensing Estimations of Vegetation Biomass.” Remote Sensing of Environment 211: 248–260. doi:10.1016/j.rse.2018.04.026.
  • Girshick, R., J. Donahue, T. Darrell, and J. Malick. 2014. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.” In 2014 Proceedings of the IEEE conference on computer vision and pattern recognition, 580–587. doi: 10.1109/CVPR.2014.81.
  • Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” In Proceedings of ICNN’95 - International Conference on Neural Networks Vol.4, 1942–1948. doi: 10.1109/ICNN.1995.488968.
  • Krizhevsky, A., I. Sutskever, and G. E. Hinton. 2017. “ImageNet Classification with Deep Convolutional Neural Networks.” Communications of the ACM 60 (6): 84–90. doi:10.1145/3065386.
  • Lecun, Y., L. Bottou, Y. Bengio, and P. Haffner. 1998. “Gradient-based Learning Applied to Document Recognition.” Proceedings of the IEEE 86 (11): 2278–2324. doi:10.1109/5.726791.
  • Li, H., S. Zhang, C. Zhang, P. Li, and R. Cropp, 2017a. “A Novel Unsupervised Levy Flight Particle Swarm Optimization (ULPSO) Method for Multispectral Remote Sensing Image Classification.” International Journal of Remote Sensing 38 (23): 6970–6992. doi:10.1080/01431161.2017.1368102.
  • Li, Q., M. Shen, Y. Gao, and Z. Zhang. 2017b. “Urban Expansion Simulation Using Modified Particle Swarm Optimization Algorithm and Cellular Automata: A Case Study of Nanjing City.” Resources and Environment in the Yangtze Basin 26: 190–197. (in Chinese). doi:10.11870/cjlyzyyhj201702004.
  • Long, J., E. Shelhamer, and T. Darrell. 2017. “Fully Convolutional Networks for Semantic Segmentation.” IEEE Transactions on Pattern Analysis & Machine Intelligence 39 (4): 640–651. doi:10.1109/TPAMI.2016.2572683.
  • McCulloch, W. S., and W. Pitts. 1943. “A Logical Calculus of Ideas Immanent in Nervous Activity.” Bulletin of Mathematical Biophysics 5: 115–133. doi:10.1007/BF02478259.
  • Natekin, A., and A. Knoll. 2013. “Gradient Boosting Machines, a Tutorial.” Frontiers in Neurorobotics 7: 1–21. doi:10.3389/fnbot.2013.00021.
  • Nebro, A. J., J. J. Durillo, J. Garcia-Nieto, C. A. Coello Coello, F. Luna, and E. Alba. 2009. “SMPSO: A New PSO-based Metaheuristic for Multi-objective Optimization.” In 2009 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MCDM 2009), 66–73. doi: 10.1109/MCDM.2009.4938830.
  • Powers, D. M. W. 2011. “Evaluation: From Precision, Recall and F-measure to ROC, Informedness, Markedness & Correlation.” Journal of Machine Learning Technologies 2 (1): 37–63.
  • Razavian, A. S., H. Azizpour, J. Sullivan, and S. Carlsson. 2014. “CNN Features Off-the-Shelf: An Astounding Baseline for Recognition.” InCVPRW ‘14 Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 512–519. doi: 10.1109/CVPRW.2014.131.
  • Zhang, C., I. Sargent, X. Pan, H. Li, A. Gardiner, J. Hare, and P. M. Atkinson. 2018a. “An Object-based Convolutional Neural Network (OCNN) for Urban Land Use Classification.” Remote Sensing of Environment 216: 57–70. doi:10.1016/j.rse.2018.06.034.
  • Zhang, C., X. Pan, H. Li, A. Gardiner, I. Sargent, J. Hare, and P. M. Atkinson. 2018b. “A Hybrid MLP-CNN Classifier for Very Fine Resolution Remotely Sensed Image Classification.” ISPRS Journal of Photogrammetry and Remote Sensing 140: 133–144. doi:10.1016/j.isprsjprs.2017.07.014.
  • Zhang, C., I. Sargent, X. Pan, H. Li, A. Gardiner, J. Hare, and P. M. Atkinson. 2019. “Joint Deep Learning for Land Cover and Land Use Classification.” Remote Sensing of Environment 221: 173–187. doi:10.1016/j.rse.2018.11.014.

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