An automated plant disease detection, Progressive Web App that will help the farmers to detect the disease in their crops and will also give insights on its treatment .

Auto Chloro is a plant disease classifier & remedies provider that uses deep learning. It can predict diseases and provide remedies. The GUI is based on Bangla Language keeping in mind that, our primary target is to create an application to predict plant diseases and provide remedies for the Bangladeshi people.

Agri-Pal is the simplest solution to aid a farmer in Agriculture - Crop and Poultry Farming. Agri-Pal is a simple Plug n Play device ensuring Disease Detection and Animal Breach Detection.

This project uses CNN to identify diseases in plants using image of their images of leaves

Farmer assistant system VCET Hackathon 2k22

A tool to scan crops and predict healthy crops, crop rust, or powdery mildews.

This repository contains code and resources for an end-to-end system designed to automate the detection and severity estimation of diseases in tomato plants.

[Archive] Please see below URL

Detect the Disease in Crop and recommend pesticides for it.

🌾 An AI-powered Crop Disease Predictor Web App that uses advanced image recognition to identify crop diseases.

This repository as all the files of the HELPMATE webpage

METADATA-FARMER ASSISTANCE WEBAPP | AI & ML

Flutter app which helps farmers take the right decisions with their crop regarding diseases. Our team's idea for GDSC solution challenge 2024

A Keras Sequential Model which predicts crop diseases of 18 crops across 55 diseases; deployed on a flask based web app.

Food Crop disease detection model using VGG16 architecture

Dataset for Potato Disease Classification

A project addressing the Mixed Pixel Problem in thermal images using AI-based Autoencoders for precision agriculture. Enables accurate crop health monitoring and early disease detection through robust deep learning algorithms and custom datasets.

Crop Disease Detection using Deep Learning employs the ResNet29 model to identify and diagnose 38 distinct crop diseases. Utilizing the Plant Village dataset, this project achieves high accuracy in detecting diseases, helping to improve agricultural sustainability through timely and automated disease detection.

Welcome to Ka-Halaman! Version 1 serves as the foundational prototype, crafted to showcase structuring of agricultural data.

repo for mini-project in 3rd semester