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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.
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.
Plant Disease Detection App. This is a simple command-line application written in Java for detecting diseases in plants. It's meant for educational purposes and serves as a basic implementation without actual image processing capabilities. How to Use. Compile the Java file: javac PlantDiseaseDetectionApp.java.
A guide for plant disease classification can serve as an invaluable resource for a beginner in the field of machine learning by offering a comprehensive overview of both the practical application of machine learning techniques and the domain-specific challenges involved in diagnosing plant health.
24 lut 2023 · The Leaf Disease Detection Flask App provides an automated solution for the detection of leaf diseases. The app uses a deep learning model to make predictions on whether the leaves are healthy or diseased.
We opte to develop an Android application that detects plant diseases. The project is broken down into multiple steps: Building and creating a machine learning model using TensorFlow with...
15 paź 2020 · To dig a little deeper, Gus Martins, Google Developer Advocate for TensorFlow, shows us how to set up a Machine Learning model to detect diseases in bean plants. Gus uses Google Colab, a cloud-hosted development tool to do transfer learning from an existing ML model hosted on TensorFlow.Hub.
