"PADDY LEAF DISEASE DETECTION PROJECT REPORT."

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Authors: Kamal Acharya
Cited by: 0

Abstract

"As one of the main ten rice delivering and devouring nations on the planet, Indiarelies enormously upon rice for its economy and for fulfilling its food needs. To guarantee solid what's more, legitimate development of the rice plants it is fundamental to distinguish any infection on schedule and before applying expected therapy to the influenced plants. Since manual recognition of sicknesses costs a huge measure of time and work, it is unavoidably reasonable to have a mechanized framework. This project presents a rice leaf sickness discovery framework utilizing AI draws near. Three of the most widely recognized rice plant infections specifically Bacterial Leaf Blight, Leaf Smut, Brown Spotinfections are identified in this work. Clear pictures of influenced rice leaves with white foundation were utilized as the info. After essential pre-handling, the dataset was prepared on with a scope of various AI calculations counting that of CNN(Convolutional Neural Network), MobileNet V2. We have collected diseased leaf images from the kaggle. We have decide to use google colaboratory for implementation of the project."

Fields of Study & Subjects

Smart Agriculture and AI Advanced Neural Network Applications Plant Virus Research Studies

Publication details

Journal / source
IEEE DataPort
Publication date
12 February 2026
Language
EN
Document type
Dataset