🌿 Detect and classify plant leaves in real-time using YOLOv8, enhancing crop health and productivity through early disease identification.

PlantGuard is a deep learning-powered plant disease detection system using ResNet-18 CNN to analyze leaf images and identify common diseases like powdery mildew and rust with real-time confidence scoring.

An IoT-based smart gardening solution with AI-powered features for monitoring, disease detection, and automation.

Detailed guide on how to train model using Python TensorFlow and the training data. Also has code to split, train, test and convert the .h5/.keras to .tflite

This app uses a deep learning model built with PyTorch to detect diseases in plants based on images of their leaves. Currently, the app supports disease detection for maize (corn), but we plan to expand to more plants in the future.

A machine learning-based project aimed at detecting and identifying plant diseases from images of affected plants. Plant Disease Detection Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

CPSC 5305 01 22FQ Introduction to Data Science Project

In this project, I trained a YOLOv8 model to detect diseases in tomato and potato plants. Accurate and timely detection of plant diseases is essential for effective crop management, and YOLOv8 offers the ability to perform real-time detection, making it a suitable choice for agricultural applications.

Folder ini berisi model CNN dan KNN dalam menganalisa penyakit tanaman cabai

Our mission is to help in identifying plant diseases efficiently. Upload an image of a plant, and our system will analyze it to detect any signs of diseases. Together, let's protect our crops and ensure a healthier harvest!

Using YOLOv8 and Detectron2 models, this project automates the detection of plant diseases from image data to facilitate early diagnosis and treatment.

This repository contains code and resources for classifying eggplant diseases using Convolutional Neural Networks (CNN). The project aims to provide a solution for identifying diseases in eggplants through image classification techniques, facilitating early detection and intervention to prevent crop losses.

This project is build using the Convolutional Neural Network which will be able to predict whether a plant is suffering from a disease.

PlantDoc is a powerful web-based platform that allows farmers to detect plant diseases by simply uploading an image.

Winner of 2021 Congressional App Challenge and OC Science Fair - https://youtu.be/cT2PHyR4q08

Android App to Detect Plant as well as Pest Detection

Plant Disease Detection using convolutional neural network. Our model can easily predict the disease of plants like Potato , Tomato , Pepper Bel and many more in the upcoming version.

The project aims to develop a system that can accurately identify various diseases in plants using machine learning algorithms. The project aims to provide a tool that can help farmers and plant pathologists quickly identify and treat plant diseases, leading to higher crop yields and better food security.

The Project aims to detect Potato Plant Disease🌱 from the uploaded images of the leaves of the before the plant gets the disease. The main aim of the repo was to learn CNN's with tensorflow.