Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps

@article{Nagasubramanian2018ExplainingHI,
  title={Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps},
  author={Koushik Nagasubramanian and Sarah Jones and Asheesh K. Singh and Arti Singh and Baskar Ganapathysubramanian and Soumik Sarkar},
  journal={CoRR},
  year={2018},
  volume={abs/1804.08831}
}
Our overarching goal is to develop an accurate and explainable model for plant disease identification using hyperspectral data. Charcoal rot is a soil borne fungal disease that affects the yield of soybean crops worldwide. Hyperspectral images were captured at 240 different wavelengths in the range of 383 1032 nm. We developed a 3D Convolutional Neural… CONTINUE READING