Name
Title | ||
|---|---|---|
Detection and discrimination of pests and diseases in winter wheat based on spectral indices and kernel discriminant analysis. |
Abstract | ||
|---|---|---|
•SVIKDA strategy is proposed for detection of multiple pests and diseases in wheat.•SVIKDA has a great capability for small-samples leaning.•SVIKDA achieved an accurate classification without loss the pathological basis.•The discriminant scores achieved robust estimation for disease indices. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.compag.2017.07.019 | Computers and Electronics in Agriculture |
Keywords | Field | DocType |
Spectral indices,Kernel discriminant analysis,Automatic detection,Winter wheat,Pests and diseases | Remote sensing,Artificial intelligence,Powdery mildew,Canopy,Computer vision,Vegetation,Discriminant,Kernel Fisher discriminant analysis,Hyperspectral imaging,Linear discriminant analysis,Engineering,Statistics,Cross-validation | Journal |
Volume | ISSN | Citations |
141 | 0168-1699 | 6 |
PageRank | References | Authors |
0.54 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yue Shi | 1 | 15 | 3.77 |
| Wenjiang Huang | 2 | 179 | 51.84 |
| Juhua Luo | 3 | 51 | 9.00 |
| Linsheng Huang | 4 | 26 | 6.49 |
| Xian-Feng Zhou | 5 | 54 | 9.35 |