Research Portal

Multimodal Learning for Classification of Solar Radio Spectrum

Research output: Contribution to conference › Paper

Standard Standard

Multimodal Learning for Classification of Solar Radio Spectrum. / Chen, Z.; Ma, L.; Xu, L. et al.
2015. 1035-1040 Paper presented at IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015.

Research output: Contribution to conference › Paper

HarvardHarvard

Chen, Z, Ma, L, Xu, L, Weng, Y & Yan, YH 2015, 'Multimodal Learning for Classification of Solar Radio Spectrum', Paper presented at IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015, 3/01/01 pp. 1035-1040. https://doi.org/10.1109/SMC.2015.187

APA

Chen, Z., Ma, L., Xu, L., Weng, Y., & Yan, Y. H. (2015). Multimodal Learning for Classification of Solar Radio Spectrum. 1035-1040. Paper presented at IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015. https://doi.org/10.1109/SMC.2015.187

CBE

Chen Z, Ma L, Xu L, Weng Y, Yan YH. 2015. Multimodal Learning for Classification of Solar Radio Spectrum. Paper presented at IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015. https://doi.org/10.1109/SMC.2015.187

MLA

Chen, Z. et al. Multimodal Learning for Classification of Solar Radio Spectrum. IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015, 03 Jan 0001, Paper, 2015. https://doi.org/10.1109/SMC.2015.187

VancouverVancouver

Chen Z, Ma L, Xu L, Weng Y, Yan YH. Multimodal Learning for Classification of Solar Radio Spectrum. 2015. Paper presented at IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015. doi: 10.1109/SMC.2015.187

Author

Chen, Z. ; Ma, L. ; Xu, L. et al. / Multimodal Learning for Classification of Solar Radio Spectrum. Paper presented at IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015.

RIS

TY - CONF

T1 - Multimodal Learning for Classification of Solar Radio Spectrum

AU - Chen, Z.

AU - Ma, L.

AU - Xu, L.

AU - Weng, Y.

AU - Yan, Y.H.

PY - 2015/10/9

Y1 - 2015/10/9

N2 - This paper proposes the first attempt to utilize multi-modal learning method for the representation learning of the solar radio spectrums. The solar radio signals sensed from different frequency channels, which present different characteristics, are regarded as different modalities. We employ a multimodal neural network to learn the representations of the solar radio spectrum, which can distinguish the differences and learn the interactions between different modalities. The original solar radio spectrums are firstly pre-processed, including normalization, denoising, channel competition and etc., before being fed into the multimodal learning network. Experimental results have demonstrated that the proposed multimodal learning network can learn the representation of the solar radio spectrum more effectively, and improve the classification accuracy.

AB - This paper proposes the first attempt to utilize multi-modal learning method for the representation learning of the solar radio spectrums. The solar radio signals sensed from different frequency channels, which present different characteristics, are regarded as different modalities. We employ a multimodal neural network to learn the representations of the solar radio spectrum, which can distinguish the differences and learn the interactions between different modalities. The original solar radio spectrums are firstly pre-processed, including normalization, denoising, channel competition and etc., before being fed into the multimodal learning network. Experimental results have demonstrated that the proposed multimodal learning network can learn the representation of the solar radio spectrum more effectively, and improve the classification accuracy.

U2 - 10.1109/SMC.2015.187

DO - 10.1109/SMC.2015.187

M3 - Paper

SP - 1035

EP - 1040

T2 - IEEE International Conference on Systems, Man, and Cybernetics (SMC), City University Hong Kong, OCT 09-12, 2015

Y2 - 3 January 0001

ER -