Image augmentation improves few-shot classification performance in plant disease recognition. (arXiv:2208.12613v1 [cs.CV])

With the world population projected to near 10 billion by 2050, minimizing
crop damage and guaranteeing food security has never been more important.
Machine learning has been proposed as a solution to quickly and efficiently
identify diseases in crops. Convolutional Neural Networks typically require
large datasets of annotated data which are not available on demand. Collecting
this data is a long and arduous process which involves manually picking,
imaging, and annotating each individual leaf. I tackle the problem of plant …

arxiv augmentation classification cv disease image performance