There are 14 repositories under plant-disease-detection topic.
Dataset used in "PlantDoc: A Dataset for Visual Plant Disease Detection" accepted in CODS-COMAD 2020
Farmassist is a smart farming app for IoT and AI-powered plant disease detection. It is built with Flutter and uses Firebase as its backend.
Bases on Leaf images we are trying to predict plant disease using convolutional neural network. PyTorch implementation
A plant disease detector (classifier) based on the PlantVillage dataset
An all purpose flutter app for farmers made under Food and Agriculture theme in Accelathon hackathon
An application that provides complete assistance to farmers right from sowing to harvesting. Its features include plant disease detection, crop recommendation, real-time API support for environment analysis, detailed crop-cost analysis, buy/sell/rent farming equipment and an interactive farmers' community.
This repo contains the python codes of my final thesis "Analysis of leaf species and detection of diseases using image processing and machine learning methods".
A project to train and evaluate different dnn models for plant disease detection problem, tackle the problem of scarce real-life representative data, experiment with different generative networks and generate more plant leaf image data and implement segmentation pipeline to avoid miss-classification due to unwanted input
Plant disease detection and Solution using Image Classification
Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".
Rudraksh - Blending Tech with Nature's Essence, Unveiling Plant Health
Dataset Analysis & CNN Models Optimization for Plant Disease Classification.
Upload leaf image🌱 and predict the plant disease.
Computer Vision Live detection of plant diseases
Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".
Saathi - Crop recommendation using ML and plant disease identification using CNN and transfer-learning approach
This is a deep-learning-powered forum for farmers. Its main features are leaf disease detection, providing remedies for diseases, and related posts aggregation.
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
Dataset Analysis and CNN Models Optimization for Plant Disease Classification.
We created a system that can help maintain home plants or even a full farm — giving our farmers the power of automated AI system to sustain their farm health. Indian agriculture farmers generally suffer due to the low production of crops. The problems lie in conveying a proper message and guidance to maintain their fields efficiently.
Transfer-Learning based Sugarcane Leaf Disease Detection Using DenseNet201 Architecture
An application that for farmers to detect the type of plant or crops, detect any kind of diseases in them. The app sends the image of the plant to the server where it is analysed using CNN classifier model. Once detected, the disease and its solutions are displayed to the user
A comprehensive project utilizing CNN and Deep Learning to detect and classify diseases in plants, enabling farmers and experts to prevent outbreaks and protect crop yield.
Plant disease detection using VGG16 model, which is a pre-trained model that has been trained on a large dataset of images.
PLANT DISEASE DETECTION USING CNN
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.
detecting disease in plants' leaves using transfer learning: Inception v3 model.
An app to detect and classify plant disease
Plant disease detection on PlantVillage dataset using EfficientNetV2-B0
A simple Plant disease detector APP, using image classification (Machine Learning) technique.
This is a deep learning project in agriculture domain that detect plants diseases
FoliumScope is a machine learning model which detects the plants disease, developed by ADG Team – Harshit, Izhan, Nihal. This project is for the Agrithon conducted by VIT
A ResNet 34-based Algorithm for Robust Plant Disease Detection with 99.2% Accuracy Across 39 Different Classes of Plant Leaf Images.
Embrace limited and imperfect training datasets in plant disease recognition using deep learning.