Artificial intelligence reveals environmental constraints on colour diversity in insects

@article{Wu2019ArtificialIR,
  title={Artificial intelligence reveals environmental constraints on colour diversity in insects},
  author={Shipher Wu and C. Chang and Guan-Shuo Mai and D. Rubenstein and Chenming Yang and Yu-Ting Huang and Hsu-Hong Lin and Li-Cheng Shih and Sheng-wei Chen and S. Shen},
  journal={Nature Communications},
  year={2019},
  volume={10}
}
  • Shipher Wu, C. Chang, +7 authors S. Shen
  • Published 2019
  • Geography, Medicine
  • Nature Communications
  • Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning—a form of artificial intelligence—can reveal subtle but robust patterns of colour feature variation along an ecological gradient, as well as help identify the underlying mechanisms generating this biogeographic pattern. Using over 20,000 images with precise GPS locality information belonging to nearly 2,000 moth species from Taiwan, our deep learning model generates a… CONTINUE READING
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