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.
API for the plant disease recognition artificial inteligence project which I collaborated on as a member of Team fort in the NaijaHacks hackaton.
Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".
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.
Computer Vision Live detection of plant diseases
Web Application which predicts Plant's Disease using ML Models
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.
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.
Dataset Analysis and CNN Models Optimization for Plant Disease Classification.
🌱🔎 This is my graduation project. The objective is to detect the disease in the coffee leaf and the contamination percentage.
Website for online plant diseases analysis from images with advanced search engine.
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.
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.
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.
This mobile application helps farmers and gardeners diagnose diseases in their petchay (Bok Choy) plants using a Convolutional Neural Network (CNN) algorithm. By analyzing images of the plant leaves, the app can detect signs of disease, providing early warnings and suggesting remedies to maintain healthy crops. It’s a simple, tech-powered solution.
Pytorch implementation of CL-ViT and FF-ViT models
A Scrapper built with Scrapy for downloading information of Plant Pest and Disease Details.
AgroGuard is a deep-learning-based application that helps us identify different diseases in plants and provides timely cures.
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