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A project to train and evaluate different dnn models for plant disease detection problem, tackle the problem of scarce real-life representative data, experiment with different generative networks and generate more plant leaf image data and implement segmentation pipeline to avoid miss-classification due to unwanted input
PlanteD is an innovative plant leaf disease detection app developed using the powerful Flutter framework, combining the prowess of Artificial Intelligence (AI) and Machine Learning (ML). Designed for plant enthusiasts, gardeners, and farmers, PlanteD revolutionizes the way we identify and combat leaf diseases, ensuring healthier plants.
Plant Disease Detection App. This is a simple command-line application written in Java for detecting diseases in plants. It's meant for educational purposes and serves as a basic implementation without actual image processing capabilities. How to Use. Compile the Java file: javac PlantDiseaseDetectionApp.java.
17 gru 2021 · This study aims to develop an android application to detect and identify plant diseases through deep convolutional neural network.
1 mar 2023 · approach for identifying plant disease regions, feature extraction (texture, color, etc.), and classification, adopt the automated extracted image features and classification using deep learning
Our project will develop an open-source web application that leverages advanced Convolutional Neural Networks to provide accurate and efficient plant disease detection and diagnosis, facilitating agricultural productivity, and serving as an educational tool for technology and agriculture enthusiasts.
6 sty 2022 · This project comprises of CNN and LSTM models, the CNN component of the project has demonstrated remarkable accuracy, achieving a 98.4% success rate in identifying plant diseases from...
