Enhancing pine wilt disease detection with synthetic data and external attention-based transformers

The catastrophic effects of Pine Wilt Disease (PWD) and the lack of a defined cure make it a danger to the world’s forests. The early detection of PWD becomes essential when establishing efficient approaches to mitigation. However, collecting data, labelling, and proposing a system for PWD detection is a challenge. This work presents an innovative PWD system and uses synthetic data sets to overcome these challenges. In particular, it emphasises two contributions: (1) the implementation of a multi-head external attention mechanism focused on improving computational effectiveness and model performance, and (2) the integration of synthetic data to address the problem of data scarcity in PWD detection. To solve…

• NR
  National Research Foundation of Korea
• MO
  Ministry of Science and ICT, South Korea
• IF
  Institute for Information and Communications Technology Promotion

  Awards: IITP-2024-RS-2024-00438056, RS-2023-00218176