Aurora Sequence Classification Based on Deep Learning

Hao Zhang; Changhong Chen

doi:10.3788/LOP55.111504

[1] Wang Q, Liang J, Hu Z J et al. Spatial texture based automatic classification of dayside aurora in all-sky images[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 72, 498-508(2010). http://www.sciencedirect.com/science/article/pii/S1364682610000441

[2] Yang Q J, Hu Z J. An automatic auroral classification method based on morphological characteristics[J]. Scientia Sinica (Terrae), 47, 252-260(2017).

[3] Han B, Qiu W L. Aurora images classification via features salient coding[J]. Journal of Xidian University, 40, 180-186(2013).

[4] Han B, Jia Z H, Gao X B. Improved PCANet for aurora images classification[J]. Journal of Xidian University, 44, 83-88(2017).

[5] Yang Q J, Liang J M, Hu Z J et al. Auroral sequence representation and classification using hidden Markov models[J]. IEEE Transactions on Geoscience and Remote Sensing, 50, 5049-5060(2012). http://ieeexplore.ieee.org/document/6208859/

[6] Xu B, Chen C, Gan Z et al. Aurora sequences classification and aurora events detection based on hidden conditional random fields. [C]∥Chinese Conference on Pattern Recognition, Springer Singapore, 404-415(2016).

[7] Han B, Song Y, Gao X et al. Dynamic aurora sequence recognition using Volume Local Directional Pattern with local and global features[J]. Neurocomputing, 184, 168-175(2016). http://dl.acm.org/citation.cfm?id=2910114.2910190

[8] Song Y T, Han B, Gao X B. Tensor based dynamic textures model for aurora sequences classification[J]. Journal of Nanjing University (Natural Science), 52, 184-193(2016).

[9] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥Advances in Neural Information Processing Systems, 1097-1105(2012).

[10] Hochreiter S, Schmidhuber J. Long short-term memory[J]. Neural Computation, 9, 1735-1780(1997).

[11] Matsukawa T, Suzuki E. Person re-identification using CNN features learned from combination of attributes. [C]∥International Conference on Pattern Recognition, IEEE, 2428-2433(2017).

[12] SimonyanK, ZissermanA.Two-stream convolutional networks for action recognition in videos[C]∥International Conference on Neural Information Processing Systems, MIT Press, 2014: 568-576.

[13] Donahue J, Hendricks L A, Guadarrama S et al. Long-term recurrent convolutional networks for visual recognition and description. [C]∥IEEE Conference on Computer Vision and Pattern Recognition, 2625-2634(2015).

[14] Ye G L, Sun S Y, Gao K J et al. Nighttime pedestrian detection based on faster region convolution neural network[J]. Laser & Optoelectronics Progress, 54, 081003(2017).

[15] Zou Y B, Zhou W L, Chen X Z. Research of laser vision seam detection and tracking system based on depth hierarchical feature[J]. Chinese Journal of Lasers, 44, 0402009(2017).

[16] Xu L, Zhao H T, Sun S Y. Monocular infrared image depth estimation based on deep convolutional neural networks[J]. Acta Optica Sinica, 36, 0715002(2016).

[17] Wu S C, Zhao H T, Sun S Y. Depth estimation from monocular infrared video based on bi-recursive convolutional neural network[J]. Acta Optica Sinica, 37, 1215003(2017).

[18] Xu Y, Lu Y. Adaptive weighted fusion: A novel fusion approach for image classification[J]. Neurocomputing, 168, 566-574(2015). http://www.sciencedirect.com/science/article/pii/S0925231215007687

[19] Deng J, Dong W, Socher R et al. ImageNet: a large-scale hierarchical image database. [C]∥IEEE Conference on Computer Vision and Pattern Recognition, 248-255(2009).

[20] Hu Z J, Yang H, Huang D et al. Synoptic distribution of dayside aurora: multiple-wavelength all-sky observation at Yellow River Station in Ny-Ålesund, Svalbard[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 71, 794-804(2009). http://www.sciencedirect.com/science/article/pii/S1364682609000339

[21] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. [C]∥International Conference on Learning Representations, 1-14(2015).

[22] Ioffe S, Szegedy C. Batch normalization: Accelerating deep network training by reducing internal covariate shift. [C]∥International Conference on Machine Learning, 448-456(2015).

[23] Kingma D P, Ba J. Adam: a method for stochastic optimization. [C]∥3rd International Conference for Learning Representations(2015).

[24] Wang Q, Hu H Q, Hu Z J et al. A method for detecting the change of auroral activities based on the all-sky image sequence[J]. Chinese Journal of Geophysics, 58, 3038-3047(2015).