Multimodal deep learning for solar radio burst classification

作者：

Highlights：

• Multimodal deep learning for solar radio burst classification is proposed.

• AE together with the structured regularization is used to enforce and learn the modality-specific sparsity and density of each modality.

• The proposed network can effectively learn the representation of the solar radio spectrum.

摘要

Highlights•Multimodal deep learning for solar radio burst classification is proposed.•AE together with the structured regularization is used to enforce and learn the modality-specific sparsity and density of each modality.•The proposed network can effectively learn the representation of the solar radio spectrum.

论文关键词：Multimodal learning,Solar radio spectrum,Classification

论文评审过程：Received 31 January 2016, Revised 20 April 2016, Accepted 22 April 2016, Available online 10 May 2016, Version of Record 13 October 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.04.013