Dataset Analysis and CNN Models Optimization for Plant Disease Classification.
-
Updated
Sep 8, 2022 - HTML
Dataset Analysis and CNN Models Optimization for Plant Disease Classification.
ML based Smart Crop Recommendation System with Disease Identification, utilizing CNNs. It aids farmers in selecting crops, managing diseases, and boosts productivity by integrating weather and geolocation APIs.
petchay doctor AI Mobile Application
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.
🌱🔎 This is my graduation project. The objective is to detect the disease in the coffee leaf and the contamination percentage.
A Scrapper built with Scrapy for downloading information of Plant Pest and Disease Details.
The identification of plant disease is the premise of the prevention of plant disease efficiently and precisely in a complex environment. Machine Learning algorithm this work attempt to predict in an earlier stage and outcomes are better.
A CNN model for detecting leaf diseases.
PlanteD is an innovative plant leaf disease detection app developed using the powerful Flutter framework, combining the prowess of Artificial Intelligence (AI) and Machine Learning (ML). Designed for plant enthusiasts, gardeners, and farmers, PlanteD revolutionizes the way we identify and combat leaf diseases, ensuring healthier plants.
Identifies the leaf diseases with the help of an android application just with a single snapshot of the leaf or any saved picture of the diseased leaf.
AgroGuard is a deep-learning-based application that helps us identify different diseases in plants and provides timely cures.
Website for online plant diseases analysis from images with advanced search engine.
Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".
Computer Vision Live detection of plant diseases
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.
Web Application which predicts Plant's Disease using ML Models
API for the plant disease recognition artificial inteligence project which I collaborated on as a member of Team fort in the NaijaHacks hackaton.
Performing Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For detection of Diseased Leaf and thus helping the increase in crop yield.
Add a description, image, and links to the plant-disease-identification topic page so that developers can more easily learn about it.
To associate your repository with the plant-disease-identification topic, visit your repo's landing page and select "manage topics."