Dataset used in "PlantDoc: A Dataset for Visual Plant Disease Detection" accepted in CODS-COMAD 2020

Bases on Leaf images we are trying to predict plant disease using convolutional neural network. PyTorch implementation

Farmassist is a smart farming app for IoT and AI-powered plant disease detection. It is built with Flutter and uses Firebase as its backend.

A plant disease detector (classifier) based on the PlantVillage dataset

An all purpose flutter app for farmers made under Food and Agriculture theme in Accelathon hackathon

An application that provides complete assistance to farmers right from sowing to harvesting. Its features include plant disease detection, crop recommendation, real-time API support for environment analysis, detailed crop-cost analysis, buy/sell/rent farming equipment and an interactive farmers' community.

This repo contains the python codes of my final thesis "Analysis of leaf species and detection of diseases using image processing and machine learning methods".

Plant disease detection and Solution using Image Classification

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

Upload leaf image🌱 and predict the plant disease.

Saathi - Crop recommendation using ML and plant disease identification using CNN and transfer-learning approach

Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".

👨🏻‍🌾 An Expert System for smart farming which provides the farmers with best solutions and hardware matching their needs exactly, with the ability to monitor and control the hardware remotely through the website UI in real-time.

CropCareAI is an AI-powered web application built using Flask to assist plant enthusiasts, farmers, and researchers in identifying and diagnosing plant diseases using pretrained Machine Learning models.

A comprehensive project utilizing CNN and Deep Learning to detect and classify diseases in plants, enabling farmers and experts to prevent outbreaks and protect crop yield.

Rudraksh - Blending Tech with Nature's Essence, Unveiling Plant Health

An application that for farmers to detect the type of plant or crops, detect any kind of diseases in them. The app sends the image of the plant to the server where it is analysed using CNN classifier model. Once detected, the disease and its solutions are displayed to the user

Dataset Analysis & CNN Models Optimization for Plant Disease Classification.

Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".

Computer Vision Live detection of plant diseases