Abstract:
Plant diseases pose a significant risk to both food security and the health of green
spaces. However, identifying these diseases quickly remains a challenge in many
regions due to inadequate infrastructure and limited development. Fortunately, the
combination of widespread internet access and recent advancements in computer
vision, particularly through deep learning, has opened up new possibilities for
diagnosing diseases based on images. By utilizing a publicly available dataset
containing images of healthy and diseased plant leaves gathered under controlled
conditions, we can train a deep convolutional neural network to recognize various
plant diseases. This approach, which involves training deep learning models on large
and accessible image datasets, offers a promising pathway to enable global-scale crop
disease diagnosis with the assistance of networks.
