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Coconut Leaf Diseases Identification System Using Image Processing

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dc.contributor.author Abeywickrama, Yasiru
dc.date.accessioned 2022-12-16T08:47:36Z
dc.date.available 2022-12-16T08:47:36Z
dc.date.issued 2022
dc.identifier.citation Abeywickrama, Yasiru (2022) Coconut Leaf DIseases Identification System Using IMage Processing. BEng. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2016245
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1132
dc.description.abstract "Sri Lanka's agriculture sector has traditionally been a direct contributor to the national economy, centered on important crops such as Tea, Rubber, and Coconut. Sri Lankan coconut, in particular, is extremely popular and in high demand around the world. Sri Lanka benefits greatly from coconut exports. However, in Sri Lanka, coconut leaf diseases are playing an increasingly important role, causing the trees' cultivation to decline. To control these illnesses, domain specialists in the field of coconut farming can be contacted, although this is a challenging task due to their limited availability. To identify coconut leaf illnesses and reduce damage, the system was built utilizing image processing and CNN (Convolution Neural Network). The author built the dataset with the help of subject specialists at the Coconut Research Institute. The pre-processed images used in the dataset were mounted to a mode and then trained. The model was trained several times and test accuracy was tested and the model was trained until a very good test accuracy was obtained." en_US
dc.language.iso en en_US
dc.subject Coconut leaf Diseases en_US
dc.subject Deep Learning en_US
dc.subject Image Classification en_US
dc.subject Image recognition en_US
dc.title Coconut Leaf Diseases Identification System Using Image Processing en_US
dc.type Thesis en_US


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