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Wheat seed quality assessment based on convolutional neural network algorithm

Abstract

Wheat seed quality assessment based on convolutional neural network algorithm

Kovalev A.V., Isaeva A.S.

Incoming article date: 12.11.2021

The article proposes a method for analyzing and assessing the quality of wheat seeds by classifying their images using artificial intelligence, namely a convolutional neural network. The architecture of a deep convolutional neural network was proposed, an image base was created for training and testing the proposed neural network, training and testing of the neural network was carried out in Tensorflow. Conclusions about the efficiency of image classification are made and areas of use of the proposed method for analyzing and assessing the quality of wheat seeds are proposed.

Keywords: convolutional neural networks, artificial intelligence, image classification