In agriculture product classification, “standards” are often subjective and heterogeneous. Below is a list of some use cases that would allow to automate the use of your operators' experience through a solution based on neural networks.
1) Classification of foods into categories and sub-categories;
eg: Distinction between macroclasses (between zucchini and cucumbers) and/or fine classification (between Granny Smith and Fuji)
2) Automatic analysis of faults in the assembly line or in a precise context;
eg: Identification of defects without having to specify the type (mold, rotten, damages, etc.) in the assembly line or detection of malformations in cheeses using X-rays (without having to open them)
3) Precise application of chemicals in industrial or open field conditions;
eg: Application of herbicides on weeds only and application of pesticides only on the cultures of interest.