Disease Mapping for Arecanut Tree using CNN

Author(s)	Thyagaraju G S
Country	India
Abstract	Arecanut is a significant crop in India, with Karnataka accounting for over 80% of its cultivation. The crop is prone to various diseases, including kole roga, Pentatomid bug (Tigane Roga), yellow leaf disease, root grub, and anabe roga. This study presents a system designed to map arecanut diseases in specific locations onto a geographical web map and accurately recognize the disease. The recognition module employs a CNN-based deep learning approach, while the web interface and mapping functionalities are developed using Python and the Django framework. As a case study, the system was tested in villages around Sirsi, including Vrgasara, Agasala, and Puttanamane. The proposed system achieved a validation accuracy of 90% for detecting kole roga in the provided images.
Keywords	koleroga, arecanut, convolution neural network
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-12
Cite This	Disease Mapping for Arecanut Tree using CNN - Thyagaraju G S - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32675
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.32675
Short DOI	https://doi.org/g8vghs

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