Digital Repository

Plant Leaf Disease Prediction

Show simple item record

dc.contributor.author Kalideen, Jawith
dc.date.accessioned 2023-01-20T05:43:46Z
dc.date.available 2023-01-20T05:43:46Z
dc.date.issued 2022
dc.identifier.citation Kalideen, Jawith (2022) Plant Leaf Disease Prediction. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2018229
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1493
dc.description.abstract "The growers and agricultural experts who labor so hard to develop and create a hunger-free community are the focus of this research endeavor. They don't get the respect they deserve for what they genuinely need. This effort will assist them in reducing stress and healing a few of their frequent ailments. To meet our project 's aims, we use a bunch of data science elements. Where any personal contacts are eliminated, machine learning is commonly used. Several difficult realworld issues can be simply handled with machine learning, even if we don't expressly program. Evaluating the vital information between the ones that have previously been saved and the ones that have been submitted for investigation is also a lengthy operation. This research may serve as a springboard for developing apps to address farming concerns in today's fast-paced, technologically advanced society, where classical and environmentally beneficial concepts coexist. This achievement shall undoubtedly clear the path for a healthy farming society. " en_US
dc.language.iso en en_US
dc.subject Plant Leaf Disease en_US
dc.subject Prediction Using Machine Learning en_US
dc.title Plant Leaf Disease Prediction en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Advanced Search

Browse

My Account