This project aims developing system that can identify and categorize diseases in plant leaves from images. This process integrates various stages from data collection to deployment, utilizing advanced machine learning techniques to improve agricultural productivity and plant health.

AgroGuard is a deep-learning-based application that helps us identify different diseases in plants and provides timely cures.

This Django-based REST API facilitates the detection of diseases on plant leaves, aiding in the identification of leaf diseases.

Master thesis project

Plant Disease Detection Using CNN

A method for paprika disease severity assessment.

Detecting diseases in maize plant leaves using convolutional neural network

Eggplant biotic stress detection app using CNN

GreenGuardian is an innovative Flutter app designed to empower users with the ability to swiftly identify and address plant diseases. Leveraging the robust Haar Cascade algorithm for image processing and disease detection, this app simplifies the process by allowing users to capture or select images of plant leaves directly from their mobile device

This model learns all the features of 48 different kinds of plants (Healthy and diseased) from the PlantVillage Dataset, and identifies the type of disease and the plant when you input any image in the model.

petchay doctor AI Mobile Application

Classify pictures of cassava leaves into 1 of 4 disease categories (or healthy)

Traditional-ML-Plant-Disease-Detection refers to the use of traditional machine learning algorithms for detecting and identifying diseases in plants.

I have developed a project using a CNN model to detect diseases in three plants: potato, tomato, and pepper. Despite limited resources, I trained separate models for each disease and successfully integrated them into a Streamlit app. The accuracy achieved on these three plants is remarkably high.

Embrace limited and imperfect training datasets in plant disease recognition using deep learning.

A ResNet 34-based Algorithm for Robust Plant Disease Detection with 99.2% Accuracy Across 39 Different Classes of Plant Leaf Images.

A simple Plant disease detector APP, using image classification (Machine Learning) technique.

Welcome to the Plant Disease Classifier Deployment repository! This project integrates cutting-edge technologies to develop a sophisticated plant disease classifier. Leveraging TensorFlow for model creation and ReactJS for the web interface, this project offers an innovative solution for identifying plant diseases swiftly and accurately.

This is a deep learning project in agriculture domain that detect plants diseases

FoliumScope is a machine learning model which detects the plants disease, developed by ADG Team – Harshit, Izhan, Nihal. This project is for the Agrithon conducted by VIT