Computer vision and neural networks to help detect crop diseases

A research team from Skoltech and Saint-Petersburg State University of Aerospace Instrumentation have presented a paper in which they pioneered an alternative method for detecting decayed and moldy apples at the post-harvest stage, when fruits are stored and then delivered to the customer. A computer vision system will determine different defects at the early stage, when they can be invisible to the human eye. The paper is published in the journal Entropy.