Convolutional neural network in rice disease recognition: accuracy, speed and lightweight.

ABSTRACT: There are many rice diseases, which have very serious negative effects on rice growth and final yield. It is very important to identify the categories of rice diseases and control them. In the past, the identification of rice disease types was completely dependent on manual work, which required a high level of human experience. But the method often could not achieve the desired effect, and was difficult to popularize on a large scale. Convolutional neural networks are good at extracting localized features from input data, converting low-level shape and texture features into high-level semantic features. Models trained by convolutional neural network technology based on existing data can extract common features of data and make the framework have generalization ability. Applying ensemble le

SUBMITTER: Ning H 

PROVIDER: S-EPMC10646333 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature