Using Deep Learning for Image-Based Plant Disease Detection

Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis. Using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify 14 crop species and 26 diseases (or absence thereof). The trained model achieves an accuracy of 99.35% on a held-out test set, demonstrating the feasibility of this approach.…

• UO
  University of Pennsylvania
• PS
  Pennsylvania State University
• ÉP
  École Polytechnique Fédérale de Lausanne
• HI
  Huck Institutes of the Life Sciences