Name
Title | ||
|---|---|---|
An Image Recognition Algorithm of Soybean Diseases and Insect Pests Based on Migration Learning and Deep Convolution Network. |
Abstract | ||
|---|---|---|
In order to extract the leaf features of soybean diseases and insect pests, reduce the complexity of the image model of soybean diseases and insect pests, and solve the over fitting phenomenon caused by the insufficient number of samples, a classification model of convolution neural network based on transfer learning technology is proposed, and the bottom features are gradually upgraded to abstract high-level features by using the multi-layer structure of convolution network with mature training Good characteristic learning ability. To enhance the data of soybean plant diseases and insect pests, extract the features of the enhanced leaf images, and classify the images by using the deep convolution neural network. The experimental results show that the method has high accuracy and robustness in soybean pest detection. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IWCMC48107.2020.9148331 | IWCMC |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingyuan Xin | 1 | 0 | 0.34 |
| Yong Wang | 2 | 0 | 0.34 |