Abstract
Plant disease is one of the important threat factors that hinder the normal growth and development of plants. The intelligent identification of plant disease species has become increasingly important in the agricultural field. In This paper, the open-source data set including Black rot, bacterial spot, rust, and healthy leaves are used to train the ResNet model. And the transfer learning algorithm is applied on ResNet to establish a plant disease recognition model with good versatility and high training efficiency. The experiment results show that the disease identification accuracy of the transfer learning model is 83.75%, which is much higher than that of the traditional ResNet-101 model. Therefore, the plant disease recognition model based on transfer learning algorithm is highly feasible.
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 callDisclaimer: 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.
