Improving classification by cocoon varieties using convolutionary neural networks

The classification of cocoons by grade is an important task in the textile industry. However, manual classification of cocoons is labor intensive and error prone. In recent years, Convolutional Neural Networks (CNNs) have been widely used in image processing tasks and demonstrate high classification accuracy. This article discusses the application of convolutional neural networks to classify cocoons by variety, and discusses additional applications of this technology in the field of image processing.