Open Access
| Issue |
MATEC Web Conf.
Volume 246, 2018
2018 International Symposium on Water System Operations (ISWSO 2018)
|
|
|---|---|---|
| Article Number | 03046 | |
| Number of page(s) | 5 | |
| Section | Parallel Session II: Water System Technology | |
| DOI | https://doi.org/10.1051/matecconf/201824603046 | |
| Published online | 07 December 2018 | |
- S. Yu, C. Xu, and S. Jia, “Convolutional neural networks for hyperspectral image classification,” Neurocomputing, 219: 88–98, (2017) [CrossRef] [Google Scholar]
- T. Chan, K. Jia, S. Gao, J. Lu, Z. Zeng, Y. Ma, “PCANet: A Simple Deep Learning Baseline for Image Classification?,” IEEE Transactions on Image Processing, vol. 24. pp: 5017-5032, (2015) [CrossRef] [Google Scholar]
- R. Liu, and T. Lu, “Character Recognition Based on PCANet,” 2016 15th International Symposium on Parallel and Distributed Computing(ISPDC), pp: 364-367, (2016) [CrossRef] [Google Scholar]
- C. Chen, D. Wang, and H. Wang, “Scene Character Recognition Using PCANet,” ICIMCS 2015: 65:1-65:4, (2015) [Google Scholar]
- F. Melgani, and L. Bruzzone, “Classification of hyperspectral remote sensing images with support vector machines,” IEEE Trans. Geosci. Remote Sens., vol. 42, no. 8, pp. 1778-1790, (2004) [NASA ADS] [CrossRef] [Google Scholar]
- M. Chi, and L. Bruzzone, “Semisupervised classification of hyperspectral images by SVMs optimized in the primal,” IEEE Trans. Geosci. Remote Sens., vol. 45, no. 6, pp. 1870-1880, (2007) [CrossRef] [Google Scholar]
- J. Li, J. M. Bioucas-Dias, and A. Plaza, “Semisupervised hyperspectral image classification using soft sparse multinomial logistic regression,” IEEE Geosci. Remote Sens. Lett., vol. 10, no. 2, pp. 318-322, (2013) [CrossRef] [Google Scholar]
- B. Pan, Z. Shi, and X. Xu, “MugNet: Deep learning for hyperspectral image classification using limited samples,” ISPRS, vol. 145, Part A, pp. 108-119, (2018) [CrossRef] [Google Scholar]
- F. Wang, R. Zhang, and Q. Wu, “Hyperspectral image classification based on PCA network”, IEEE 2016 8th WHISPERS, pp: 1-4, (2016) [Google Scholar]
- M. Fauvel, Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C. Tilton, “Advances in spectralspatial classification of hyperspectral images,” Proceedings of the IEEE, vol. 101, no. 3, pp. 652-675, (2013) [CrossRef] [Google Scholar]
- K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun, “What is the best multi-stage architecture for object recognition,” in ICCV, (2009) [Google Scholar]
- A. Krizhevsky, I. Sutskever, and G. Hinton, “Imagenet classification with deep convolutional neural network,” in NIPS, (2012) [Google Scholar]
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