Abstract
The work is aimed at developing a convolutional neural network for automated sorting of apples by size, weight, and visual defects. Studies were carried out using an experimental installation, which was used to collect and markup the data array. The neural network was written in Python using the Tensorflow and Keras libraries. The created model exhibited an accuracy of 96.88 % in recognition results on delayed data. A sorter device model was designed to implement the trained algorithm in the sorting production cycle.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: LETI Transactions on Electrical Engineering & Computer Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
