Multimodal abnormal and dead laying hen detection using transformer-based model

In commercial caged laying hen farming, daily monitoring for abnormal and dead hens is critical. The crowded and low-light conditions often render unimodal images insufficient for accurate detection. To address this, we propose a Transformer-based multimodal abnormal and dead laying hen detection method tailored to actual caged environments. First, we propose a multimodal chicken image fusion network based on the Mamba, names MCIFusion-Mamba. A Mamba-based image fusion network and a fusion loss function that simultaneously considers image similarity, texture, intensity, and saliency objectives are proposed to achieve better spatial perception and retain more complete target semantic information. The fused…

• NN
  National Natural Science Foundation of China

  Award: 32502968
• NK
  National Key Research and Development Program of China

  Award: 2021YFD1300101
• BA
  Basic and Applied Basic Research Foundation of Guangdong Province

  Award: 2023A1515110691