Name
Abstract | ||
|---|---|---|
•A method for detecting leaf level tea anthracnose based on hyperspectral imaging.•Two new disease indices were developed and effectively used.•A two-dimensional thresholding strategy was proposed for detecting disease scabs.•A satisfactory accuracy was achieved at leaf level (98%) and pixel level (94%). |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.compag.2019.105039 | Computers and Electronics in Agriculture |
Keywords | Field | DocType |
Tea plant,Anthracnose,Hyperspectral image,ISODATA classification | Computer vision,Pattern recognition,Disease prevention,Hyperspectral imaging,Pixel,Artificial intelligence,Engineering,Thresholding | Journal |
Volume | ISSN | Citations |
167 | 0168-1699 | 2 |
PageRank | References | Authors |
0.40 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Yuan | 1 | 3 | 1.12 |
| Peng Yan | 2 | 2 | 0.40 |
| Wenyan Han | 3 | 2 | 0.40 |
| Yanbo Huang | 4 | 50 | 8.86 |
| Bin Wang | 5 | 7 | 5.53 |
| Jingcheng Zhang | 6 | 45 | 10.39 |
| Haibo Zhang | 7 | 2 | 0.40 |
| Zhiyan Bao | 8 | 2 | 0.40 |