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http://13.232.72.61:8080/jspui/handle/123456789/5273Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Anju, Shaji | - |
| dc.contributor.author | Chaitra, B. | - |
| dc.contributor.author | Roopashree, C. | - |
| dc.contributor.author | Lathashree, K. P. | - |
| dc.contributor.author | Gowtham, S. | - |
| dc.date.accessioned | 2022-01-28T09:48:18Z | - |
| dc.date.available | 2022-01-28T09:48:18Z | - |
| dc.date.issued | 2021-08 | - |
| dc.identifier.citation | Anju, Shaji., Chaitra, B., Roopashree, C., Lathashree, K. P., & Gowtham, S. (2021). Various Approaches for Plant Disease Detection. Iconic Research and Engineering Journal, 5(2), 26-29. | en_US |
| dc.identifier.uri | http://13.232.72.61:8080/jspui/handle/123456789/5273 | - |
| dc.description | use only for the academic purpose | en_US |
| dc.description.abstract | Plant diseases are quite natural because of environment and climate conditions. Diseases are often difficult to regulate. To scale back the loss timely detection of disease is necessary. Automated detection of plant leaf disease is advantageous because it reduces the expense and time required in monitoring large fields. This paper provides survey on various plant leaf disease classification techniques. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IRE Journal | en_US |
| dc.subject | Disease Identification | en_US |
| dc.subject | Machine Learning Techniques | en_US |
| dc.subject | Image Processing | en_US |
| dc.subject | Deep Learning Techniques | en_US |
| dc.title | Various Approaches for Plant Disease Detection | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Articles | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Various Approaches for Plant Disease Detection.pdf | 136.46 kB | Adobe PDF | View/Open |
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