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.

AgriTech is an AI-powered web platform that offers crop recommendations, yield prediction, disease detection, and collaborative tools to empower farmers and promote smart, sustainable agriculture.

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

Plant disease detection and Solution using Image Classification

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.

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.

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".

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

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.

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

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.

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

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

Dataset Analysis & CNN Models Optimization for Plant Disease Classification.

Computer Vision Live detection of plant diseases

Developed a Plant Species Identification system using Flask and the ResNet9 model. This tool accurately identifies plant species from images, making it indispensable for botany enthusiasts. Key skills involved include Convolutional Neural Networks (CNN), HTML, CSS, and Python.

Web Application which predicts Plant's Disease using ML Models

A computer vision-based project that uses YOLOv8 to detect and classify plant leaves in real time, helping identify healthy and diseased plants efficiently to support smart agriculture solutions.

🌾 AI-powered plant disease detection app for farmers in West Nusa Tenggara, Indonesia. Built with Flutter, Azure Custom Vision & Azure OpenAI.

This is a deep-learning-powered forum for farmers. Its main features are leaf disease detection, providing remedies for diseases, and related posts aggregation.

Transfer-Learning based Sugarcane Leaf Disease Detection Using DenseNet201 Architecture

Plantex 🌿 detects plant diseases with 99% accuracy using TensorFlow/Keras 🤖. It offers disease info 📚, product recommendations 🛒, and organic waste exchange 🔄. An AI chatbot 🤖 aids user interaction. Promoting sustainability 🌱 in smart cities.

Dataset Analysis and CNN Models Optimization for Plant Disease Classification.

The identification of plant disease is the premise of the prevention of plant disease efficiently and precisely in a complex environment. Machine Learning algorithm this work attempt to predict in an earlier stage and outcomes are better.

AI-powered plant disease detection system using computer vision, deep learning, and ESP32-CAM for real-time crop health monitoring and analysis.