A Multimodal Fusion-Based LNG Detection for Monitoring Energy Facilities (Student Abstract)

Junchi Bin, Choudhury A. Rahman, Shane Rogers, Shan Du, Zheng Liu

AAAI 2022 pp. 12917-12918

doi:10.1609/AAAI.V36I11.21595 /aaai/2022/bin2022aaai-multimodal/

Abstract

Fossil energy products such as liquefied natural gas (LNG) are among Canada's most important exports. Canadian engineers devote themselves to constructing visual surveillance systems for detecting potential LNG emissions in energy facilities. Beyond the previous infrared (IR) surveillance system, in this paper, a multimodal fusion-based LNG detection (MFLNGD) framework is proposed to enhance the detection quality by the integration of IR and visible (VI) cameras. Besides, a Fourier transformer is developed to fuse IR and VI features better. The experimental results suggest the effectiveness of the proposed framework.

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Cite

Text

Bin et al. "A Multimodal Fusion-Based LNG Detection for Monitoring Energy Facilities (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21595

Markdown

[Bin et al. "A Multimodal Fusion-Based LNG Detection for Monitoring Energy Facilities (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/bin2022aaai-multimodal/) doi:10.1609/AAAI.V36I11.21595

BibTeX

@inproceedings{bin2022aaai-multimodal,
  title     = {{A Multimodal Fusion-Based LNG Detection for Monitoring Energy Facilities (Student Abstract)}},
  author    = {Bin, Junchi and Rahman, Choudhury A. and Rogers, Shane and Du, Shan and Liu, Zheng},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {12917-12918},
  doi       = {10.1609/AAAI.V36I11.21595},
  url       = {https://mlanthology.org/aaai/2022/bin2022aaai-multimodal/}
}