| dc.contributor.author | Mojumdar, Mayen Uddin | |
| dc.contributor.author | Chakraborty, Narayan Ranjan | |
| dc.date.accessioned | 2021-08-19T07:24:51Z | |
| dc.date.available | 2021-08-19T07:24:51Z | |
| dc.date.issued | 2020-10-15 | |
| dc.identifier.uri | http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6004 | |
| dc.description.abstract | Agribusiness and its efficiency have a decent effect on the financial development of each nation. In Agriculture, leaf ailments have become an issue because it may a create basic decline in both quality and measure of agrarian output. In this manner, computerized acknowledgement of ailments on leaves assumes a significant job in the farming area. This paper gives a basic and computationally capable strategy utilized for leaf sickness recognizable proof and reviewing utilizing Image processing and computer vision. In this study, a computerized approach is created to distinguish deformities of Malabar nightshade and perceive infections by utilizing machine vision-based picture preparing method which is actualized in MATLAB including an AI calculation with the Multiclass SVM classifier. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.subject | Diseases | en_US |
| dc.subject | Computer vision | en_US |
| dc.subject | Support vector machines | en_US |
| dc.subject | Agriculture | en_US |
| dc.subject | Logistics | en_US |
| dc.subject | Sensitivity | en_US |
| dc.subject | Image segmentation | en_US |
| dc.title | A Computer Vision Technique to Detect Scab on Malabar Nightshade | en_US |
| dc.type | Article | en_US |