Irish potato leaves disease detection system using a smartphone application
dc.contributor.author | Mugume, Ian | |
dc.contributor.author | Nakayiga, Priscilla J. | |
dc.contributor.author | Okello, Andrew Peters | |
dc.contributor.author | Akakunda, Shivan | |
dc.date.accessioned | 2022-04-13T07:34:04Z | |
dc.date.available | 2022-04-13T07:34:04Z | |
dc.date.issued | 2022-01 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12281/11678 | |
dc.description.abstract | Early detection of leaf diseases in Irish potato plants is a tedious or challenging task. This is because it requires huge or lots of time as well as skilled labour. Skilled labour who are the experts in the field of plant leaf disease detection and classification are at times hired by farmers but this tends to be costly or expensive to pay them to get advise after diagnosis and also time consuming for cases where the experts are very few to cover most parts of the country and are also in far distant places. This delay can lead to losses in the farmers’ gardens. In this research, we propose a machine learning model being embedded in an Android application to aid in the early detection of leaf diseases in Irish potatoes. The proposed machine learning model provides an accuracy of 99.75%, recall of 99.66% and precision of 99.66%. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Plant diseases | en_US |
dc.subject | Disease detection | en_US |
dc.subject | Leaf diseases | en_US |
dc.subject | Irish potatoes | en_US |
dc.title | Irish potato leaves disease detection system using a smartphone application | en_US |
dc.type | Thesis | en_US |