Examination is carried out on the basis of the analysis of the following features: color, shape, size, presence of visible defects and damages.
The system is able to recognize diseases and defects by at least 30 criteria for each type of product.
To increase the accuracy of identifying signs of marriage, production is photographed with white and ultraviolet light.
The system is compact and located on the office table *.
To manage the system requires 1 specialist without the skills of an expert in the field of acceptance of fresh fruit or vegetable products.
The system is able to detect a fault with an accuracy of at least 95%.
Get the results of the examination both in real time mode and in the form of a survey report drawn up according to international standards.
Thanks to the laid down principles of machine learning, the system can be trained and tuned for a short period of time in order to carry out an examination of any kind of products.
The system will ensure compatibility with any conveyor solutions and will allow for the detection and examination of both static and moving objects **.
To increase the accuracy and reliability of the examination in the future, it is planned to connect to the system gas analyzers, nitrate meters, thermal imagers, scales.