Smart System  for Tomato Leaf Disease Prediction  with Severity Analysis

Fernando, Melisha

dc.contributor.author	Fernando, Melisha
dc.date.accessioned	2025-06-12T04:15:07Z
dc.date.available	2025-06-12T04:15:07Z
dc.date.issued	2024
dc.identifier.citation	Fernando, Melisha (2024) Smart System for Tomato Leaf Disease Prediction with Severity Analysis. BSc. Dissertation, Informatics Institute of Technology	en_US
dc.identifier.issn	20200675
dc.identifier.uri	http://dlib.iit.ac.lk/xmlui/handle/123456789/2513
dc.description.abstract	This project addresses the need for accurate, automated detection and assessment of tomato leaf diseases to improve crop quality. Additionally, an algorithm quantifies disease severity by analyzing lesion coverage and discoloration, aiding in effective disease management.	en_US
dc.language.iso	en	en_US
dc.subject	Computer vision	en_US
dc.subject	Machine learning	en_US
dc.subject	Convolutional Neural networks	en_US
dc.title	Smart System for Tomato Leaf Disease Prediction with Severity Analysis	en_US
dc.type	Thesis	en_US