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

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

[AAAI-22] Student Abstract and Poster Program
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.

Sessions where this paper appears

  • Poster Session 6

    Sat, February 26 8:45 AM - 10:30 AM (+00:00)
    Red 4
    Add to Calendar

  • Poster Session 7

    Sat, February 26 4:45 PM - 6:30 PM (+00:00)
    Red 4
    Add to Calendar