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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.
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.
🌿 Plant Disease Detection from Images 🌿. 📋 Project Overview. Our project focuses on creating an intuitive Streamlit application that empowers users to upload images of plant leaves for accurate identification of plant diseases.
Using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify 14 crop species and 26 diseases (or absence thereof).
27 paź 2020 · This article addresses the plant disease identification task by state-of-the-art three deep learning meta-architectures prominently Faster Region-based Convolutional Neural Network (RCNN), Single Shot MultiBox Detector (SSD), and Region-based Fully Convolutional Networks (RFCN).
AI and Machine Learning techniques to detect plant diseases. This research survey provides a comprehensive understanding of common plant leaf diseases, evaluates traditional and deep learning techniques for disease detection, and summarizes avail-able datasets. It also explores Explainable AI (XAI) to enhance
5 sty 2020 · In this study, we present an AI-based plant monitoring system for detecting and classifying plant diseases using visual images. Our deep learning models are trained on plant images...
