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.
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.
This is a project i made for my MINOR in college , which is based on Machine Learning and focuses on Image Processing .Feel free to make changes .
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.
Folder ini berisi model CNN dan KNN dalam menganalisa penyakit tanaman cabai
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
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
Winner of 2021 Congressional App Challenge and OC Science Fair - https://youtu.be/cT2PHyR4q08
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!
An IoT-based smart gardening solution with AI-powered features for monitoring, disease detection, and automation.
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.
This project is build using the Convolutional Neural Network which will be able to predict whether a plant is suffering from a disease.
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.
🌿 Detect and classify plant leaves in real-time using YOLOv8, enhancing crop health and productivity through early disease identification.
Apple Diseases Classificaiton with Google Teachable Machine
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.
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